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Integration of Bass Enhancement and Active Noise Control System in Automobile Cabin

Integration of Bass Enhancement and Active Noise Control System in Automobile Cabin Hindawi Publishing Corporation Advances in Acoustics and Vibration Volume 2008, Article ID 869130, 9 pages doi:10.1155/2008/869130 Research Article Integration of Bass Enhancement and Active Noise Control System in Automobile Cabin 1 1 2 Liang Wang, Woon Seng Gan, and Sen M. Kuo School of Electrical and Electronic Engineering, College of Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798 Department of Electrical Engineering, Northern Illinois University, DeKalb, IL 60115, USA Correspondence should be addressed to Liang Wang, wang0136@ntu.edu.sg Received 29 December 2007; Accepted 5 March 2008 Recommended by Marek Pawelczyk With the advancement of digital signal processing technologies, consumers are more concerned with the quality of multimedia entertainment in automobiles. In order to meet this demand, an audio enhancement system is needed to improve bass reproduction and cancel engine noise in the cabins. This paper presents an integrated active noise control system that is based on frequency-sampling filters to track and extract the bass information from the audio signal, and a multifrequency active noise equalizer to tune the low-frequency engine harmonics to enhance the bass reproduction. In the noise cancellation mode, a maximum of 3 dB bass enhancement can be achieved with significant noise suppression, while higher bass enhancement can be achieved in the bass enhance mode. The results show that the proposed system is effective for solving both the bass audio reproduction and the noise control problems in automobile cabins. Copyright © 2008 Liang Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. INTRODUCTION cabins. In some practical applications, it prefers to enhance some preselected noise components to extract important Noise control and the high-quality bass reproduction in sound information. For example, the driver may want automobile cabins are two interrelated problems. The later to know how the engine is working when driving. Due can be difficult due to the high-level noise present and to its flexibility of amplifying or attenuating noises with the size of the loudspeakers that can be installed inside predetermined levels at certain frequencies, active noise equalizer (ANE) [4] systems and other similar algorithms [5– the cars. Traditional passive noise control techniques are only efficient at high frequencies. For the low-frequency 7] have potential applications. engine noises, passive techniques become costly and bulky, High-quality audio reproduction in cabins can be diffi- cult due to the engine noise and low-frequency performance which are not suitable for the use in automobile cabins. Due to its effectiveness in reducing low-frequency noise, the of the loudspeakers. With the flexibility of ANE system, active noise control (ANC) [1] technique has received much we propose a novel method to solve this problem. Instead attention since 1980s [2, 3]. of trying to cancel the engine noise entirely, the proposed On the other hand, with the advancement of multimedia integrated system equalizes the engine-noise harmonics digital signal processing (DSP) technologies, high-quality based on the bass information to enhance the low- frequency audio reproduction is becoming possible for the automo- part of audio signal. The main challenges are to track the biles. However, there are many challenges in reproducing frequencies of engine harmonics and to tune these harmon- ics to match the bass components of audio signal.In order high-quality bass in cars due to the limited space and acoustic properties, and the low-frequency noise present in to integrate active noise control with bass enhancement, the the cabins. proposed system uses frequency-sampling filter (FSF) [8] TheANC techniquesgenerally producegood perfor- and multifrequency ANE [4] to tune the engine harmonics, mance in canceling the narrowband engine noise. However, and convert the annoying low-frequency noise into desired it does not offer complete control over the engine noise in audio bass components. 2 Advances in Acoustics and Vibration d(n) e(n) Acoustic Noise P(z) Σ source domain Sync Electrical −1 domain signal S(z) x (n) Sine wave w (n) generator 1 − β Canceling y(n) branch Balancing x (n) branch w (n) 90 1 S(z) S(z) S(z) e (n) LMS Figure 1: Block diagram of single-frequency ANE system. Audio Bass Tachometer extraction Post Multifrequency processing ANE Figure 2: System block diagram inside the automobile cabin. The remainder of this paper is structured as follows. (i) cancellation mode (β = 0): ANE functions as the Section 2 presents the narrowband ANE system, followed conventional narrowband ANC; by a description of the proposed system in Section 3. (ii) attenuation mode (0 <β < 1): the amount of Simulation results under different driving conditions are attenuation is determined by β. Therefore, it is given in Section 4,and Section 5 concludes this paper. possible to retain some portion of the noise at the selected frequency; 2. NARROWBAND ACTIVE NOISE EQUALIZER (iii) neutral mode (β = 1): the noise passes through the ANE system without attenuation; The single-frequency narrowband ANE [4]systemisbased on an adaptive notch filter using the filtered-X least mean (iv) enhancement mode (β> 1): the ANE functions as square (FXLMS) [1] algorithm. As shown in Figure 1, the an amplifier that enhances the noise component with secondary output is split into two branches: the canceling amount determined by β. branch and the balancing branch. A pseudoerror e (n) is used to trick the adaptive filter to converge to a desirable state 3. PROPOSED SYSTEM IN AUTOMOBILE CABINS determined by the user. The pseudoerror can be expressed as A proposed system in car cabins that integrates bass enhancement and active noise equalizer is shown in Figure 2. e (n) = d(n) − y(n) s(n). (1) This system can be divided into three subsystems: (i) the “bass extraction” block extracts bass components from After convergence, the pseudoerror approaches zero. How- the car audio system based on the engine speed; (ii) the ever, the actual residual noise e(n)converges to “postprocessing” block processes; these bass components to e(n) = d(n) − (1 − β)y(n) s(n) ≈ βd(n), match with frequencies of engine harmonics; and (iii) the (2) “multifrequency ANE” block implements a multifrequency where β is known as the gain factor determined by the user. ANE that enhances desired low-frequency audio components Depending on the gain factor β, ANE can be classified using equalized engine harmonics. A detailed overview of into four operation modes [4]: these subsystems is described as follows. Liang Wang et al. 3 Tachometer Audio Amp1 LPF k Normalizer FSF Power estimation Multifrequency ANE Post processing HPF Amp2 Figure 3: Audio signal extraction block diagram. 2/N reconfiguration and computational efficiency are important x(n) − N considerations for designing the filter bank. The FSF is −1 −N chosen to meet these requirements. It is based on sampling − H (0) y(n) Σ Σ Σ a desired amplitude spectrum to obtain the corresponding filter coefficients. The number of FSF channels equals to 2 −1 r z the number of predominant engine-noise harmonics, where −1 each channel corresponds to one engine harmonic. As shown in Figure 4, the unique characteristic of the FSF structure −1 allows recursive implementation of finite-impulse response 2πk r cos filters, leading to both computational efficiency and fast − N H (k) ΣΣ online reconfiguration. The transfer function of the FSF is −1 2 expressed as −1 z H (z) −1 2 1 − r cos(2πk/N )z L −N k −1 = 1 − r z (−1) H (k) , −1 2 −2 H (N/2) N 1 − 2r cos(2πk/N )z + r z − −r k≤N/2 ΣΣ (3) 2 −1 r z where N is the filter length, H (k) is frequency sample value −1 at channel k,and r is a radius of pole that is slightly less than unity. Equation (3) shows that the FSF has N parallel Figure 4: Frequency-sampling filter block diagram. bandpass filters with center frequencies at 2πk/N,where k = 0, 1,... , N − 1. Therefore, the parameter N controls center frequencies of all bandpass filters. The following sections further describe how to design an FSF for a particular engine. 3.1. Bass extraction 3.1.1. Engine RPM and the fundamental The audio signal components that will be enhanced are those frequency of engine noise close to the engine-noise components, which are related to the engine revolutions per minute (RPM). Because the This section investigates the fundamental and firing frequen- engine RPM is time varying, the engine-noise components cies of a 4-stroke engine. A sampling frequency of 1.5 kHz change accordingly, thus the filters must self-configure is selected for the FSF processing block. This sampling according to the engine RPM to extract the desired audio sig- frequency restricts the range of engine noise to 600 Hz. For nal components. In other words, the filter’s center frequency a 4-stroke engine, the fundamental frequency is the product should be tuned by the engine RPM. of the firing frequency and number of the cylinders, where As shown in Figure 3, the audio signal is passed through the firing frequency is a low pass filter with a cutoff frequency at 500 Hz, and the audio signal is decimated to a lower sampling frequency of 1 RPM firing frequency = × Hz. (4) 1.5 kHz. Therefore, a lower computational load is achieved 2 60 for processing bass information of the audio signal. To utilize engine noise for enhancing bass reproduction, The fundamental frequency of engine noise is the fourth extraction of the audio signal at frequencies of engine harmonic of the firing frequency. Depending on the engine harmonics is needed. This requires a bank of passband noise profile, the harmonics selected can be different. When filters align with predominant engine harmonics. Fast online higher frequency harmonics are selected, this range will be 4 Advances in Acoustics and Vibration resolution of the filter. Therefore, the optimal resolution is determined by the frequency range of the engine noise. Offline calibration is required for different engines to select the proper value of k, which is set to the center frequency of fundamental engine noise, and correspondingly determine 0.4 the frequency resolution. Frequency index k − 2 kk +2 3.2. Postprocessing Figure 5: Diagram of FSF filter setting for fundamental engine The signal power estimation is performed before sending to noise frequency. postprocessing block. The process can be expressed as P (n) = λP (n − 1) + (1 − λ)x (n), (7) x x lowered accordingly. For most cars and with the objective where P (n) is the signal power, x(n) is the current sample, of bass enhancement, the sampling frequency of 1.5 kHz is and λ is known as the smoothing parameter or forgetting reasonable. factor, typically set between 0.9 to 0.999. There are many options for the postprocessing block. Users can perform 3.1.2. Parametric factor different kinds of equalization. This paper proposes two schemes. The bass enhancement scheme is designed for There are two methods in determining the main parameters higher amplification of equalized engine noise, and the to control the filtering and center frequencies of FSF. One is noise cancellation scheme is designed for more engine noise to set the filter length N as a constant value and change each reduction. of the frequency sample values H (k). However, this approach requires changing multiple sample values during online filter reconfiguration. On the other hand, if we first set the relative 3.2.1. Bass enhancement scheme frequency samples at certain values, it is possible to achieve The bass enhancement scheme emphasizes on the enhance- the reconfiguration by changing only the FSF filter length N . ment of bass components in the audio signal. Using the For example, when we set the filter H (k)at k = 10 to coincide power estimation results obtained from previous block, the with the fundamental frequency of noise, the filter length can gain factors β , i = 1, 2,... , Ns in the ANE systems can be the be derived as calculated as Fs 1 RPM Fs × 10 × 30 × 10 = × × 4 =⇒ N = . (5) N 2 60 RPM β = P × α, i = 1, 2,... , Ns,(8) i i When the RPM is 2500, the corresponding filter length is 180. where P is the power of the FSF’s output that corresponding It is also important to point out that the FSF does not incur to the engine harmonic frequency, and α is a constant a higher computational load when the filter length increases. that controls the volume of the sound in order to mix the This is because most frequency samples H (k)are zero and tuned engine noise with the original audio output. Users can only few frequency samples defined in the passband require tune α to different levels of bass enhancement. The variable computation. Ns is the number of predominant engine noise harmonics which is dependent on the particular engine type. If the in 3.1.3. Transition band sample value cabin loudspeakers are incapable in reproducing the signal at engine noise fundamental frequency, the perception of bass Rabiner et al. proposed some typical values for the coeffi- can still be enhanced by other harmonics due to the famous cients in the transition band [9]. In the case of designing “missing fundamental” phenomenon. the FSF for handling typical RPM from 1000 to 2500, the In ordertoset the valueof α that determines β ,it filter length ranges from 180 to 450. If three samples are is important to derive the relationship between the sound used to define the frequency samples in the passband, the pressure level of the audio signal and engine noise. In typical optimum value for transition band is found to be 0.4 [10] audio system, the sound pressure level ranges from 50 dB to The illustration is shown in Figure 5. 80 dB. On the other hand, the engine noise level in a cabin ranges from 45 dB to 75 dB [9]. For a 16-bit audio signal, 3.1.4. Selecting suitable filter length/frequency resolution which is normalized to unit, the sound pressure level is stated as As the sampling frequency Fs is 1500 Hz, the frequency resolution for FSF is Fs/N . According to the relationship: 2 SPL = 96 dB + 10 log x (n)dB. (9) Fs 1 RPM × k = × × 4, (6) This equation sets the maximum sound pressure level SPL N 2 60 to 96 dB when the amplitude of x(n)equalsto1. where k is the sample index that is selected to align at the To calibrate the value of factor α, it is assumed that if engine noise frequency. As a result, index k controls the the signal SPL is 60 dB, the engine noise should be neither A Liang Wang et al. 5 Acoustic domain e(n) Engine P(z) Σ noise y (n) x (n) 1 G (z) 1 1 − β Tachometer S(z) −1 . Σ . y (n) Sine wave generator 1 − β G (z) n Electrical domain x (n) S (z) Σ β 1 e (n) . 1 S (z) Σ . n e (n) ··· Bass Post Audio Amp1 LPF processing extraction Amp3 HPF Figure 6: System block diagram of the multifrequency ANE. amplified nor attenuated. According to (9) and setting SPL When the engine noise is lower than the audio signal, to 60 dB, the amplitude of the signal is computed as we keep or cancel the engine noise harmonics depending on whether the audio signal is present or not. As a result, the (SPL −96)/20 gain factor for the ANE system is either one or zero. The A = 10 ≈ 0.016. (10) maximum gain of 3 dB is achieved when the engine noise −4 level equals the audio signal level. Therefore, to achieve the The power of the signal is approximately 1.28× 10 . Setting desired gain adjustment in Section 2, a new gain scheme is β to1results in α ≈ 88. proposed as follows: 3.2.2. Noise cancellation scheme (SPL −SPL )/γ A E e ,SPL < SPL < SPL , ⎪ O A E It can be seen from the previous scheme that by tuning the β = 1, SPL < SPL < SPL , (11) O E A factor α, higher enhancement at the low frequency can be ⎪ 0, SPL < SPL , A O achieved. However, at the same time, the timbre of the orig- inal signal will also change. To fulfill the needs of enhancing bass reproduction while maintaining a balanced timbre with where SPL is the sound pressure level of audio at the significant noise cancellation, we propose another scheme corresponding engine noise harmonic frequency, SPL is the known as the noise cancellation scheme. sound pressure level of the engine noise harmonic, SPL is In this scheme, when engine noise is louder than the used as a threshold and is set to 45 dB, and γ is a constant audio signal, a proper equalized engine noise is used to governing the equalization between the gain factor and enhance the audio signal. In order to maintain a better difference between the sound pressure level of audio signal timber, this scheme does not allow any amplification of the and engine noise. engine noise, or the gain factors for engine noise harmonics To equalize the engine noise when SPL < SPL < SPL , O A E should be always smaller than one. The rationale behind this the gain factor β is chosen such that scheme is to make the amplitude of the engine harmonics equals to the corresponding amplitude of the audio signal βA = A , (12) E A at that frequency. In this way, when there is audio signal present at the engine noise harmonics, the ANE system amplifies the amplitude of the engine noise to produce a 3 dB where A is the amplitude of the engine noise and A is the E A enhancement of audio signal. amplitude of the audio signal. Substituting (9)and (11) into 6 Advances in Acoustics and Vibration (12), we have (SPL −SPL )/γ A E A e = A , E A (13) (SPL −96)/20 (SPL −SPL )/γ A E e = . (SPL −96)/20 Taking logarithm of both sides, we obtain SPL − SPL SPL − 96 SPL − 96 A E A E log e = − . (14) γ 20 20 This results in log e 1 12 3 4 5 6 78 9 = , (15) γ 20 Time Figure 7: Spectrogram of the recorded engine noise. and γ ≈ 8.6859. According to this gain factor scheme under a loud engine noise condition, it is expected to achieve both reduction of engine noise and a 3 dB bass enhancement at certain frequencies. 3.3. Multifrequency ANE system To perform the active control of the engine noise, we designed a multifrequency ANE system consisting of sev- eral independent single-frequency ANE systems connected in parallel. Each single-frequency ANE is tuned to the corresponding harmonic frequency of the engine noise. 20 The overall block diagram of the multichannel ANE is shown in Figure 6. The number of the single-frequency 10 ANE system is determined by the number of the selected predominant engine noise harmonics. Each ANE block has 0 50 100 150 200 250 300 350 400 its own gain factor tuned to the power of the related Frequency (Hz) audio component. When the audio signal is changing with time, the equalization of the low-frequency signal responds Figure 8: Power distribution of the recorded engine noise. accordingly. 4. SIMULATION RESULTS 4.1. Bass enhancement scheme Performance of the proposed system is evaluated by both The results shown in Figures 9 and 10 are the spectrograms a synthesized engine noise and a recorded in cabin engine that show bass components of audio signal before and after noise (Toyota Crown at passenger seat with the engine the process, respectively. The predominant engine noise running at around 2600 RPM). The reference signal is harmonics are attenuated (marked as circles in diagrams) generated using cosine wave with the center frequency at the when the audio is absent, and tuned according to the gain corresponding engine noise harmonic. Kim and Park showed factor shown in Figure 11, when the audio is present. in [11] that the self-generated reference could achieve good To display the tuned engine noise more clearly, the performance in ANC applications. Figures 7 and 8 show spectrogram of the tuned engine noise is shown in Figure 12. the spectrogram and power distribution of the engine noise, It is observed that the tuned engine noise has a similar respectively. For this recorded engine noise, we select two spectrogram distribution as the audio signal. predominant frequency components and an FSF is used to The proposed system is also evaluated using synthesized extract the bass audio information. engine noise to test the effectiveness at defined harmonics. In The audio signal used for the simulation is “Hotel the following simulation, the synthesized engine is running California” by The Eagles (live version). The sound clip was at 3000 RPM, with its predominant harmonic frequencies at taken from the start of the track, which consists of a bass 100, 200, 300, and 400 Hz. As seen from Figure 13, the engine drum with some audience noise. This track makes it easier noise components at 100, 300, and 400 Hz are attenuated by to focus on the bass. The sound clip and simulation results 5, 8, and 15 dB. However, a 3 dB enhancement is achieved at wave files are available at [12]. 200 Hz. The equalized engine noise is equalized to enhance Power (dB) Frequency Liang Wang et al. 7 700 700 600 600 500 500 400 400 300 300 200 200 100 100 0 0 12 3 4 5 6 78 9 12 3 4 5 6 78 9 Time Time Figure 9: Spectrogram of the sound in cabin when system off. Figure 12: Spectrogram of the tuned noise. 0 50 100 150 200 250 300 350 400 450 500 12 3 4 5 6 78 9 Frequency (Hz) Time Figure 10: Spectrogram of the sound in cabin when system on. After processing Before processing Audio Figure 13: Bass enhancement scheme with synthesized engine 4.5 noise. 3.5 the bass component of the audio signal. The gain factor value for the 200 Hz harmonic over the duration of simulation is shown in Figure 14. 2.5 4.2. Noise cancellation scheme 1.5 In this simulation, we investigate the performance of the 1 proposed system under noise cancellation scheme. The system is tested with the recorded engine noise (running at 0.5 2600 RPM) and with SPL of 75 dB. The spectrogram of this 0 engine noise is similar with those under bass enhancement 0 2000 4000 6000 8000 10000 12000 mode. Time index The tested audio file is extracted from a short speech clip. We simulate the case when the driver is listening to news or Figure 11: Gain factor for fundamental frequency. Gain factor Frequency Frequency Power (dB) Frequency 8 Advances in Acoustics and Vibration 3.5 0.25 0.2 2.5 0.15 1.5 0.1 0.05 0.5 0 500 1000 1500 2000 2500 3000 3500 4000 0 500 1000 1500 Time index Time index Figure 16: Gain factor using noise cancellation scheme. Figure 14: Gain factor (at 200 Hz) in bass enhancement scheme. 70 80 60 70 50 60 0 50 100 150 200 250 300 350 400 450 500 0 50 100 150 200 250 300 350 400 450 500 Frequency (Hz) Frequency (Hz) After processing After processing Before processing Before processing Speech Audio Figure 15: Engine noise before and after processing. Figure 17: Noise cancellation scheme with synthesized engine noise. making a phone call. The system adapts to cancel the engine 1 noise to achieve a better SNR for speech perception in the car 0.9 cabin. Engine noise before and after processing is shown in 0.8 Figure 15. It can be clearly observed that the most prominent 0.7 engine noise harmonics are reduced by 6 dB. Gain factor for the fundamental frequency over the period of simulation is 0.6 shown in Figure 16. 0.5 Similar to the bass enhancement scheme, we evaluate 0.4 the system using audio signal and the synthesized engine noise. As seen from Figure 17, the engine noise components 0.3 are significantly reduced, especially at 400 Hz since there 0.2 is very little audio component. The gain factor value for 0.1 200 Hz harmonic over the duration of simulation is shown in Figure 18. Compared with the result obtained in bass 0 500 1000 1500 enhancement scheme, it clearly shows that the gain factor Time index value is confined in the range of 0 to 1, and engine noise is never been amplified. Figure 18: Gain factor (at 200 Hz) in noise cancellation scheme. Gain factor Power (dB) Gain factor Gain factor Power (dB) Liang Wang et al. 9 5. CONCLUSION Instead of canceling the engine noise entirely, this paper presented a system that utilizes the engine noise to enhance the bass reproduction of audio signal in automobile cabins. The proposed system integrated bass extraction, audio signal processing, and active noise equalization to enhance desired bass signal and reduce noise. Several engine noises and audio signals are used to evaluate the performance of integrated audio and active noise equalization system. Simulation results showed that the proposed system can achieve audio bass reproduction and noise reduction inside the car cabins. REFERENCES [1] S.M.Kuo andD.R.Morgan, Active Noise Control Systems: Algorithms and DSP Implementations, John Wiley & Sons, New York, NY, USA, 1996. [2] M. Vaishya, “Active noise control using a single sensor input,” US patent no. 6917687, July, 2005. [3] H. Sano, T. Inoue, A. Takahashi, K. Terai, and Y. Nakamura, “Active control system for low-frequency road noise combined with an audio system,” IEEE Transactions on Speech and Audio Processing, vol. 9, no. 7, pp. 755–763, 2001. [4] S. M. Kuo and M. J. Ji, “Development and analysis of an adaptive noise equalizer,” IEEE Transactions on Speech and Audio Processing, vol. 3, no. 3, pp. 217–222, 1995. [5] J. Feng and W. S. Gan, “Adaptive active noise equaliser,” Electronics Letters, vol. 33, no. 18, pp. 1518–1519, 1997. [6] L. E. Rees and S. J. Elliott, “Adaptive algorithms for active sound-profiling,” IEEE Transactions on Audio, Speech and Language Processing, vol. 14, no. 2, pp. 711–719, 2006. [7] L.Wang, W. S. Gan,Y.K.Chong,and S. M. Kuo, “A novel approach to bass enhancement in automobile cabin,” in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP ’06), vol. 3, pp. 1216– 1219, Toulouse, France, May 2006. [8] S.M.Kuo andB.H.Lee, Real-Time Digital Signal Processing, John Wiley & Sons, New York, NY, USA, 2001. [9] D. J. Thompson and J. Dixon, “Vehicle noise,” in Advanced Applications in Acoustics, Noise and Vibration, pp. 236–291, Spon Press, London, UK, 2004. [10] L. R. Rabiner, B. Gold, and C. A. McGonegal, “An approach to the approximation problem for nonrecursive digital filters,” IEEE Transactions on Audio and Electroacoustics, vol. 18, no. 2, pp. 83–106, 1970. [11] S. Kim and Y. Park, “On-line fundamental frequency tracking method for harmonic signal and application to ANC,” Journal of Sound and Vibration, vol. 241, no. 4, pp. 681–691, 2001. [12] L. Wang, http://eeeweba.ntu.edu.sg/DSPLab/ANE/samples .html. 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Integration of Bass Enhancement and Active Noise Control System in Automobile Cabin

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Hindawi Publishing Corporation
Copyright
Copyright © 2008 Liang Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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1687-6261
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1687-627X
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10.1155/2008/869130
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Abstract

Hindawi Publishing Corporation Advances in Acoustics and Vibration Volume 2008, Article ID 869130, 9 pages doi:10.1155/2008/869130 Research Article Integration of Bass Enhancement and Active Noise Control System in Automobile Cabin 1 1 2 Liang Wang, Woon Seng Gan, and Sen M. Kuo School of Electrical and Electronic Engineering, College of Engineering, Nanyang Technological University, Nanyang Avenue, Singapore 639798 Department of Electrical Engineering, Northern Illinois University, DeKalb, IL 60115, USA Correspondence should be addressed to Liang Wang, wang0136@ntu.edu.sg Received 29 December 2007; Accepted 5 March 2008 Recommended by Marek Pawelczyk With the advancement of digital signal processing technologies, consumers are more concerned with the quality of multimedia entertainment in automobiles. In order to meet this demand, an audio enhancement system is needed to improve bass reproduction and cancel engine noise in the cabins. This paper presents an integrated active noise control system that is based on frequency-sampling filters to track and extract the bass information from the audio signal, and a multifrequency active noise equalizer to tune the low-frequency engine harmonics to enhance the bass reproduction. In the noise cancellation mode, a maximum of 3 dB bass enhancement can be achieved with significant noise suppression, while higher bass enhancement can be achieved in the bass enhance mode. The results show that the proposed system is effective for solving both the bass audio reproduction and the noise control problems in automobile cabins. Copyright © 2008 Liang Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1. INTRODUCTION cabins. In some practical applications, it prefers to enhance some preselected noise components to extract important Noise control and the high-quality bass reproduction in sound information. For example, the driver may want automobile cabins are two interrelated problems. The later to know how the engine is working when driving. Due can be difficult due to the high-level noise present and to its flexibility of amplifying or attenuating noises with the size of the loudspeakers that can be installed inside predetermined levels at certain frequencies, active noise equalizer (ANE) [4] systems and other similar algorithms [5– the cars. Traditional passive noise control techniques are only efficient at high frequencies. For the low-frequency 7] have potential applications. engine noises, passive techniques become costly and bulky, High-quality audio reproduction in cabins can be diffi- cult due to the engine noise and low-frequency performance which are not suitable for the use in automobile cabins. Due to its effectiveness in reducing low-frequency noise, the of the loudspeakers. With the flexibility of ANE system, active noise control (ANC) [1] technique has received much we propose a novel method to solve this problem. Instead attention since 1980s [2, 3]. of trying to cancel the engine noise entirely, the proposed On the other hand, with the advancement of multimedia integrated system equalizes the engine-noise harmonics digital signal processing (DSP) technologies, high-quality based on the bass information to enhance the low- frequency audio reproduction is becoming possible for the automo- part of audio signal. The main challenges are to track the biles. However, there are many challenges in reproducing frequencies of engine harmonics and to tune these harmon- ics to match the bass components of audio signal.In order high-quality bass in cars due to the limited space and acoustic properties, and the low-frequency noise present in to integrate active noise control with bass enhancement, the the cabins. proposed system uses frequency-sampling filter (FSF) [8] TheANC techniquesgenerally producegood perfor- and multifrequency ANE [4] to tune the engine harmonics, mance in canceling the narrowband engine noise. However, and convert the annoying low-frequency noise into desired it does not offer complete control over the engine noise in audio bass components. 2 Advances in Acoustics and Vibration d(n) e(n) Acoustic Noise P(z) Σ source domain Sync Electrical −1 domain signal S(z) x (n) Sine wave w (n) generator 1 − β Canceling y(n) branch Balancing x (n) branch w (n) 90 1 S(z) S(z) S(z) e (n) LMS Figure 1: Block diagram of single-frequency ANE system. Audio Bass Tachometer extraction Post Multifrequency processing ANE Figure 2: System block diagram inside the automobile cabin. The remainder of this paper is structured as follows. (i) cancellation mode (β = 0): ANE functions as the Section 2 presents the narrowband ANE system, followed conventional narrowband ANC; by a description of the proposed system in Section 3. (ii) attenuation mode (0 <β < 1): the amount of Simulation results under different driving conditions are attenuation is determined by β. Therefore, it is given in Section 4,and Section 5 concludes this paper. possible to retain some portion of the noise at the selected frequency; 2. NARROWBAND ACTIVE NOISE EQUALIZER (iii) neutral mode (β = 1): the noise passes through the ANE system without attenuation; The single-frequency narrowband ANE [4]systemisbased on an adaptive notch filter using the filtered-X least mean (iv) enhancement mode (β> 1): the ANE functions as square (FXLMS) [1] algorithm. As shown in Figure 1, the an amplifier that enhances the noise component with secondary output is split into two branches: the canceling amount determined by β. branch and the balancing branch. A pseudoerror e (n) is used to trick the adaptive filter to converge to a desirable state 3. PROPOSED SYSTEM IN AUTOMOBILE CABINS determined by the user. The pseudoerror can be expressed as A proposed system in car cabins that integrates bass enhancement and active noise equalizer is shown in Figure 2. e (n) = d(n) − y(n) s(n). (1) This system can be divided into three subsystems: (i) the “bass extraction” block extracts bass components from After convergence, the pseudoerror approaches zero. How- the car audio system based on the engine speed; (ii) the ever, the actual residual noise e(n)converges to “postprocessing” block processes; these bass components to e(n) = d(n) − (1 − β)y(n) s(n) ≈ βd(n), match with frequencies of engine harmonics; and (iii) the (2) “multifrequency ANE” block implements a multifrequency where β is known as the gain factor determined by the user. ANE that enhances desired low-frequency audio components Depending on the gain factor β, ANE can be classified using equalized engine harmonics. A detailed overview of into four operation modes [4]: these subsystems is described as follows. Liang Wang et al. 3 Tachometer Audio Amp1 LPF k Normalizer FSF Power estimation Multifrequency ANE Post processing HPF Amp2 Figure 3: Audio signal extraction block diagram. 2/N reconfiguration and computational efficiency are important x(n) − N considerations for designing the filter bank. The FSF is −1 −N chosen to meet these requirements. It is based on sampling − H (0) y(n) Σ Σ Σ a desired amplitude spectrum to obtain the corresponding filter coefficients. The number of FSF channels equals to 2 −1 r z the number of predominant engine-noise harmonics, where −1 each channel corresponds to one engine harmonic. As shown in Figure 4, the unique characteristic of the FSF structure −1 allows recursive implementation of finite-impulse response 2πk r cos filters, leading to both computational efficiency and fast − N H (k) ΣΣ online reconfiguration. The transfer function of the FSF is −1 2 expressed as −1 z H (z) −1 2 1 − r cos(2πk/N )z L −N k −1 = 1 − r z (−1) H (k) , −1 2 −2 H (N/2) N 1 − 2r cos(2πk/N )z + r z − −r k≤N/2 ΣΣ (3) 2 −1 r z where N is the filter length, H (k) is frequency sample value −1 at channel k,and r is a radius of pole that is slightly less than unity. Equation (3) shows that the FSF has N parallel Figure 4: Frequency-sampling filter block diagram. bandpass filters with center frequencies at 2πk/N,where k = 0, 1,... , N − 1. Therefore, the parameter N controls center frequencies of all bandpass filters. The following sections further describe how to design an FSF for a particular engine. 3.1. Bass extraction 3.1.1. Engine RPM and the fundamental The audio signal components that will be enhanced are those frequency of engine noise close to the engine-noise components, which are related to the engine revolutions per minute (RPM). Because the This section investigates the fundamental and firing frequen- engine RPM is time varying, the engine-noise components cies of a 4-stroke engine. A sampling frequency of 1.5 kHz change accordingly, thus the filters must self-configure is selected for the FSF processing block. This sampling according to the engine RPM to extract the desired audio sig- frequency restricts the range of engine noise to 600 Hz. For nal components. In other words, the filter’s center frequency a 4-stroke engine, the fundamental frequency is the product should be tuned by the engine RPM. of the firing frequency and number of the cylinders, where As shown in Figure 3, the audio signal is passed through the firing frequency is a low pass filter with a cutoff frequency at 500 Hz, and the audio signal is decimated to a lower sampling frequency of 1 RPM firing frequency = × Hz. (4) 1.5 kHz. Therefore, a lower computational load is achieved 2 60 for processing bass information of the audio signal. To utilize engine noise for enhancing bass reproduction, The fundamental frequency of engine noise is the fourth extraction of the audio signal at frequencies of engine harmonic of the firing frequency. Depending on the engine harmonics is needed. This requires a bank of passband noise profile, the harmonics selected can be different. When filters align with predominant engine harmonics. Fast online higher frequency harmonics are selected, this range will be 4 Advances in Acoustics and Vibration resolution of the filter. Therefore, the optimal resolution is determined by the frequency range of the engine noise. Offline calibration is required for different engines to select the proper value of k, which is set to the center frequency of fundamental engine noise, and correspondingly determine 0.4 the frequency resolution. Frequency index k − 2 kk +2 3.2. Postprocessing Figure 5: Diagram of FSF filter setting for fundamental engine The signal power estimation is performed before sending to noise frequency. postprocessing block. The process can be expressed as P (n) = λP (n − 1) + (1 − λ)x (n), (7) x x lowered accordingly. For most cars and with the objective where P (n) is the signal power, x(n) is the current sample, of bass enhancement, the sampling frequency of 1.5 kHz is and λ is known as the smoothing parameter or forgetting reasonable. factor, typically set between 0.9 to 0.999. There are many options for the postprocessing block. Users can perform 3.1.2. Parametric factor different kinds of equalization. This paper proposes two schemes. The bass enhancement scheme is designed for There are two methods in determining the main parameters higher amplification of equalized engine noise, and the to control the filtering and center frequencies of FSF. One is noise cancellation scheme is designed for more engine noise to set the filter length N as a constant value and change each reduction. of the frequency sample values H (k). However, this approach requires changing multiple sample values during online filter reconfiguration. On the other hand, if we first set the relative 3.2.1. Bass enhancement scheme frequency samples at certain values, it is possible to achieve The bass enhancement scheme emphasizes on the enhance- the reconfiguration by changing only the FSF filter length N . ment of bass components in the audio signal. Using the For example, when we set the filter H (k)at k = 10 to coincide power estimation results obtained from previous block, the with the fundamental frequency of noise, the filter length can gain factors β , i = 1, 2,... , Ns in the ANE systems can be the be derived as calculated as Fs 1 RPM Fs × 10 × 30 × 10 = × × 4 =⇒ N = . (5) N 2 60 RPM β = P × α, i = 1, 2,... , Ns,(8) i i When the RPM is 2500, the corresponding filter length is 180. where P is the power of the FSF’s output that corresponding It is also important to point out that the FSF does not incur to the engine harmonic frequency, and α is a constant a higher computational load when the filter length increases. that controls the volume of the sound in order to mix the This is because most frequency samples H (k)are zero and tuned engine noise with the original audio output. Users can only few frequency samples defined in the passband require tune α to different levels of bass enhancement. The variable computation. Ns is the number of predominant engine noise harmonics which is dependent on the particular engine type. If the in 3.1.3. Transition band sample value cabin loudspeakers are incapable in reproducing the signal at engine noise fundamental frequency, the perception of bass Rabiner et al. proposed some typical values for the coeffi- can still be enhanced by other harmonics due to the famous cients in the transition band [9]. In the case of designing “missing fundamental” phenomenon. the FSF for handling typical RPM from 1000 to 2500, the In ordertoset the valueof α that determines β ,it filter length ranges from 180 to 450. If three samples are is important to derive the relationship between the sound used to define the frequency samples in the passband, the pressure level of the audio signal and engine noise. In typical optimum value for transition band is found to be 0.4 [10] audio system, the sound pressure level ranges from 50 dB to The illustration is shown in Figure 5. 80 dB. On the other hand, the engine noise level in a cabin ranges from 45 dB to 75 dB [9]. For a 16-bit audio signal, 3.1.4. Selecting suitable filter length/frequency resolution which is normalized to unit, the sound pressure level is stated as As the sampling frequency Fs is 1500 Hz, the frequency resolution for FSF is Fs/N . According to the relationship: 2 SPL = 96 dB + 10 log x (n)dB. (9) Fs 1 RPM × k = × × 4, (6) This equation sets the maximum sound pressure level SPL N 2 60 to 96 dB when the amplitude of x(n)equalsto1. where k is the sample index that is selected to align at the To calibrate the value of factor α, it is assumed that if engine noise frequency. As a result, index k controls the the signal SPL is 60 dB, the engine noise should be neither A Liang Wang et al. 5 Acoustic domain e(n) Engine P(z) Σ noise y (n) x (n) 1 G (z) 1 1 − β Tachometer S(z) −1 . Σ . y (n) Sine wave generator 1 − β G (z) n Electrical domain x (n) S (z) Σ β 1 e (n) . 1 S (z) Σ . n e (n) ··· Bass Post Audio Amp1 LPF processing extraction Amp3 HPF Figure 6: System block diagram of the multifrequency ANE. amplified nor attenuated. According to (9) and setting SPL When the engine noise is lower than the audio signal, to 60 dB, the amplitude of the signal is computed as we keep or cancel the engine noise harmonics depending on whether the audio signal is present or not. As a result, the (SPL −96)/20 gain factor for the ANE system is either one or zero. The A = 10 ≈ 0.016. (10) maximum gain of 3 dB is achieved when the engine noise −4 level equals the audio signal level. Therefore, to achieve the The power of the signal is approximately 1.28× 10 . Setting desired gain adjustment in Section 2, a new gain scheme is β to1results in α ≈ 88. proposed as follows: 3.2.2. Noise cancellation scheme (SPL −SPL )/γ A E e ,SPL < SPL < SPL , ⎪ O A E It can be seen from the previous scheme that by tuning the β = 1, SPL < SPL < SPL , (11) O E A factor α, higher enhancement at the low frequency can be ⎪ 0, SPL < SPL , A O achieved. However, at the same time, the timbre of the orig- inal signal will also change. To fulfill the needs of enhancing bass reproduction while maintaining a balanced timbre with where SPL is the sound pressure level of audio at the significant noise cancellation, we propose another scheme corresponding engine noise harmonic frequency, SPL is the known as the noise cancellation scheme. sound pressure level of the engine noise harmonic, SPL is In this scheme, when engine noise is louder than the used as a threshold and is set to 45 dB, and γ is a constant audio signal, a proper equalized engine noise is used to governing the equalization between the gain factor and enhance the audio signal. In order to maintain a better difference between the sound pressure level of audio signal timber, this scheme does not allow any amplification of the and engine noise. engine noise, or the gain factors for engine noise harmonics To equalize the engine noise when SPL < SPL < SPL , O A E should be always smaller than one. The rationale behind this the gain factor β is chosen such that scheme is to make the amplitude of the engine harmonics equals to the corresponding amplitude of the audio signal βA = A , (12) E A at that frequency. In this way, when there is audio signal present at the engine noise harmonics, the ANE system amplifies the amplitude of the engine noise to produce a 3 dB where A is the amplitude of the engine noise and A is the E A enhancement of audio signal. amplitude of the audio signal. Substituting (9)and (11) into 6 Advances in Acoustics and Vibration (12), we have (SPL −SPL )/γ A E A e = A , E A (13) (SPL −96)/20 (SPL −SPL )/γ A E e = . (SPL −96)/20 Taking logarithm of both sides, we obtain SPL − SPL SPL − 96 SPL − 96 A E A E log e = − . (14) γ 20 20 This results in log e 1 12 3 4 5 6 78 9 = , (15) γ 20 Time Figure 7: Spectrogram of the recorded engine noise. and γ ≈ 8.6859. According to this gain factor scheme under a loud engine noise condition, it is expected to achieve both reduction of engine noise and a 3 dB bass enhancement at certain frequencies. 3.3. Multifrequency ANE system To perform the active control of the engine noise, we designed a multifrequency ANE system consisting of sev- eral independent single-frequency ANE systems connected in parallel. Each single-frequency ANE is tuned to the corresponding harmonic frequency of the engine noise. 20 The overall block diagram of the multichannel ANE is shown in Figure 6. The number of the single-frequency 10 ANE system is determined by the number of the selected predominant engine noise harmonics. Each ANE block has 0 50 100 150 200 250 300 350 400 its own gain factor tuned to the power of the related Frequency (Hz) audio component. When the audio signal is changing with time, the equalization of the low-frequency signal responds Figure 8: Power distribution of the recorded engine noise. accordingly. 4. SIMULATION RESULTS 4.1. Bass enhancement scheme Performance of the proposed system is evaluated by both The results shown in Figures 9 and 10 are the spectrograms a synthesized engine noise and a recorded in cabin engine that show bass components of audio signal before and after noise (Toyota Crown at passenger seat with the engine the process, respectively. The predominant engine noise running at around 2600 RPM). The reference signal is harmonics are attenuated (marked as circles in diagrams) generated using cosine wave with the center frequency at the when the audio is absent, and tuned according to the gain corresponding engine noise harmonic. Kim and Park showed factor shown in Figure 11, when the audio is present. in [11] that the self-generated reference could achieve good To display the tuned engine noise more clearly, the performance in ANC applications. Figures 7 and 8 show spectrogram of the tuned engine noise is shown in Figure 12. the spectrogram and power distribution of the engine noise, It is observed that the tuned engine noise has a similar respectively. For this recorded engine noise, we select two spectrogram distribution as the audio signal. predominant frequency components and an FSF is used to The proposed system is also evaluated using synthesized extract the bass audio information. engine noise to test the effectiveness at defined harmonics. In The audio signal used for the simulation is “Hotel the following simulation, the synthesized engine is running California” by The Eagles (live version). The sound clip was at 3000 RPM, with its predominant harmonic frequencies at taken from the start of the track, which consists of a bass 100, 200, 300, and 400 Hz. As seen from Figure 13, the engine drum with some audience noise. This track makes it easier noise components at 100, 300, and 400 Hz are attenuated by to focus on the bass. The sound clip and simulation results 5, 8, and 15 dB. However, a 3 dB enhancement is achieved at wave files are available at [12]. 200 Hz. The equalized engine noise is equalized to enhance Power (dB) Frequency Liang Wang et al. 7 700 700 600 600 500 500 400 400 300 300 200 200 100 100 0 0 12 3 4 5 6 78 9 12 3 4 5 6 78 9 Time Time Figure 9: Spectrogram of the sound in cabin when system off. Figure 12: Spectrogram of the tuned noise. 0 50 100 150 200 250 300 350 400 450 500 12 3 4 5 6 78 9 Frequency (Hz) Time Figure 10: Spectrogram of the sound in cabin when system on. After processing Before processing Audio Figure 13: Bass enhancement scheme with synthesized engine 4.5 noise. 3.5 the bass component of the audio signal. The gain factor value for the 200 Hz harmonic over the duration of simulation is shown in Figure 14. 2.5 4.2. Noise cancellation scheme 1.5 In this simulation, we investigate the performance of the 1 proposed system under noise cancellation scheme. The system is tested with the recorded engine noise (running at 0.5 2600 RPM) and with SPL of 75 dB. The spectrogram of this 0 engine noise is similar with those under bass enhancement 0 2000 4000 6000 8000 10000 12000 mode. Time index The tested audio file is extracted from a short speech clip. We simulate the case when the driver is listening to news or Figure 11: Gain factor for fundamental frequency. Gain factor Frequency Frequency Power (dB) Frequency 8 Advances in Acoustics and Vibration 3.5 0.25 0.2 2.5 0.15 1.5 0.1 0.05 0.5 0 500 1000 1500 2000 2500 3000 3500 4000 0 500 1000 1500 Time index Time index Figure 16: Gain factor using noise cancellation scheme. Figure 14: Gain factor (at 200 Hz) in bass enhancement scheme. 70 80 60 70 50 60 0 50 100 150 200 250 300 350 400 450 500 0 50 100 150 200 250 300 350 400 450 500 Frequency (Hz) Frequency (Hz) After processing After processing Before processing Before processing Speech Audio Figure 15: Engine noise before and after processing. Figure 17: Noise cancellation scheme with synthesized engine noise. making a phone call. The system adapts to cancel the engine 1 noise to achieve a better SNR for speech perception in the car 0.9 cabin. Engine noise before and after processing is shown in 0.8 Figure 15. It can be clearly observed that the most prominent 0.7 engine noise harmonics are reduced by 6 dB. Gain factor for the fundamental frequency over the period of simulation is 0.6 shown in Figure 16. 0.5 Similar to the bass enhancement scheme, we evaluate 0.4 the system using audio signal and the synthesized engine noise. As seen from Figure 17, the engine noise components 0.3 are significantly reduced, especially at 400 Hz since there 0.2 is very little audio component. The gain factor value for 0.1 200 Hz harmonic over the duration of simulation is shown in Figure 18. Compared with the result obtained in bass 0 500 1000 1500 enhancement scheme, it clearly shows that the gain factor Time index value is confined in the range of 0 to 1, and engine noise is never been amplified. Figure 18: Gain factor (at 200 Hz) in noise cancellation scheme. Gain factor Power (dB) Gain factor Gain factor Power (dB) Liang Wang et al. 9 5. CONCLUSION Instead of canceling the engine noise entirely, this paper presented a system that utilizes the engine noise to enhance the bass reproduction of audio signal in automobile cabins. The proposed system integrated bass extraction, audio signal processing, and active noise equalization to enhance desired bass signal and reduce noise. Several engine noises and audio signals are used to evaluate the performance of integrated audio and active noise equalization system. Simulation results showed that the proposed system can achieve audio bass reproduction and noise reduction inside the car cabins. REFERENCES [1] S.M.Kuo andD.R.Morgan, Active Noise Control Systems: Algorithms and DSP Implementations, John Wiley & Sons, New York, NY, USA, 1996. [2] M. Vaishya, “Active noise control using a single sensor input,” US patent no. 6917687, July, 2005. [3] H. Sano, T. Inoue, A. Takahashi, K. Terai, and Y. Nakamura, “Active control system for low-frequency road noise combined with an audio system,” IEEE Transactions on Speech and Audio Processing, vol. 9, no. 7, pp. 755–763, 2001. [4] S. M. Kuo and M. J. Ji, “Development and analysis of an adaptive noise equalizer,” IEEE Transactions on Speech and Audio Processing, vol. 3, no. 3, pp. 217–222, 1995. [5] J. Feng and W. S. Gan, “Adaptive active noise equaliser,” Electronics Letters, vol. 33, no. 18, pp. 1518–1519, 1997. [6] L. E. Rees and S. J. Elliott, “Adaptive algorithms for active sound-profiling,” IEEE Transactions on Audio, Speech and Language Processing, vol. 14, no. 2, pp. 711–719, 2006. [7] L.Wang, W. S. Gan,Y.K.Chong,and S. M. Kuo, “A novel approach to bass enhancement in automobile cabin,” in Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP ’06), vol. 3, pp. 1216– 1219, Toulouse, France, May 2006. [8] S.M.Kuo andB.H.Lee, Real-Time Digital Signal Processing, John Wiley & Sons, New York, NY, USA, 2001. [9] D. J. Thompson and J. Dixon, “Vehicle noise,” in Advanced Applications in Acoustics, Noise and Vibration, pp. 236–291, Spon Press, London, UK, 2004. [10] L. R. Rabiner, B. Gold, and C. A. McGonegal, “An approach to the approximation problem for nonrecursive digital filters,” IEEE Transactions on Audio and Electroacoustics, vol. 18, no. 2, pp. 83–106, 1970. [11] S. Kim and Y. Park, “On-line fundamental frequency tracking method for harmonic signal and application to ANC,” Journal of Sound and Vibration, vol. 241, no. 4, pp. 681–691, 2001. [12] L. Wang, http://eeeweba.ntu.edu.sg/DSPLab/ANE/samples .html. 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