Generalized Sidelobe Canceller Research Articles

GSC 구조의 시공간 모노펄스 시스템

For a target echo containing interference, it is very difficult to improve the performance of a monopulse radar with spatial domain processing, because the statistical property of interference cannot be exclusively obtained. This paper proposes a monopulse system that has a generalized sidelobe canceller(GSC) filter-based time domain processor as a preprocessor prior to conventional monopulse spatial processing. We analytically show the procedure of time-space signal processing running in the system, and assess its performance through simulation. In particular, the performance dependence on the number of taps in the main channel filter and the estimation error in Doppler frequency are assessed by comparison with those of existing systems.

Blind adaptive constrained constant modulus algorithms based on unscented Kalman filter for beamforming

This work proposes constrained constant modulus unscented Kalman filter (CCM-UKF) algorithm and its low-complexity version called reduced-rank constrained constant modulus unscented Kalman filter (RR-CCM-UKF) algorithm for blind adaptive beamforming. In the generalized sidelobe canceller (GSC) structure, the proposed algorithms are devised according to the CCM criterion. Firstly, the cost function of the constrained optimization problem is transformed to suit the Kalman filter-style state space model. Then, the optimum weight vector of the beamformer can be estimated by using the recursive formulas of UKF. In addition, the a priori parameters of UKF (system and measurement noises) are processed adaptively in the implementation. Simulation results demonstrate that the proposed algorithms outperform the existing methods in terms of convergence speeds, output signal-tointerference- plus-noise ratios (SINRs), mean-square deviations (MSDs) and robustness against steering mismatch.

Robust Generalized Sidelobe Canceller with an Eigenanalysis-Based Blocking Matrix

In acoustic environments with strong background noise and interferences, the generalized sidelobe canceller (GSC) suffers from signal distortion and reduced amount of noise suppression since the blocking matrix cannot produce pure noise reference due to unavoidable direction of arrival (DOA) mismatch. In this paper, a generalized sidelobe canceller robust to DOA mismatch is proposed. It employs eigenanalysis to reconstruct the interference-plus-noise covariance matrix with the possible DOA region of signal of interest (SOI). The reconstructed matrix is provided for the MaxSINR beamforming and subsequent blocking matrix construction. The designed blocking matrix can minimize the signal leakage meanwhile maximize the noise and interference power for further noise and interference suppression. Numerical simulation results show that compared with the alternatives, the proposed GSC has better interference suppression capability and lower SOI distortion in situations without precise DOA of SOI.

Comparison of LMS and NLMS algorithm with the using of 4 Linear Microphone Array for Speech Enhancement.

In this paper, we have presented the design, implementation and comparison result of Least Mean Square (LMS) algorithm and Normalized LMS (NLMS) algorithm using a 4 channel microphone array for noise reduction as well as speech enhancement. Adaptive sub band Generalized Side lobe Canceller (GSC) beam former has been used for experiment and analysis. Tested results were done by using one speech signal and a small number of noise sources. The side lobe canceller was evaluated with the adaptation of LMS and NLMS. The overall development of Signal to Noise Ratio (SNR) has been determined from the input and output powers of signal and noise, with signal only as input and noise, as input to the GSC. The NLMS algorithm considerably improves speech quality with noise suppression levels of up to 13 dB, while the LMS algorithm is giving up to 10 dB. In different ways of SNR measure was under various types of blocking matrix, step sizes and various noise locations. The whole process will be used for hands-free telephony, video conferencing etc. in a noisy environment.

Comparison of LMS and NLMS algorithm with the using of 4 Linear Microphone Array for Speech Enhancement.

In this paper, we have presented the design, implementation and comparison result of Least Mean Square (LMS) algorithm and Normalized LMS (NLMS) algorithm using a 4 channel microphone array for noise reduction as well as speech enhancement. Adaptive sub band Generalized Side lobe Canceller (GSC) beam former has been used for experiment and analysis. Tested results were done by using one speech signal and a small number of noise sources. The side lobe canceller was evaluated with the adaptation of LMS and NLMS. The overall development of Signal to Noise Ratio (SNR) has been determined from the input and output powers of signal and noise, with signal only as input and noise, as input to the GSC. The NLMS algorithm considerably improves speech quality with noise suppression levels of up to 13 dB, while the LMS algorithm is giving up to 10 dB. In different ways of SNR measure was under various types of blocking matrix, step sizes and various noise locations. The whole process will be used for hands-free telephony, video conferencing etc. in a noisy environment.

Broadband Adaptive Beamforming of Conformal Arrays for Wireless Communications Based on Generalized Sidelobe Canceller

Conformal arrays are increasingly used in recent wireless communication systems due to their flexibility in mounting on arbitrary surfaces. Many of such systems require working with broadband signals. However, designing conformal arrays has been limited mostly to pattern synthesis techniques due to the complexity imposed by the different contribution of individual antenna patterns to the overall array response. Such pattern synthesis techniques greatly confine the application of the beamformer in dynamic environments since they are fundamentally non-adaptive data independent methods. In this article, the conventional space–time broadband generalized sidelobe canceller (GSC) is used to develop an adaptive method for an arbitrarily-shaped conformal array. The constraint matrix assumed for the main beam of the conventional GSC structure is modified to incorporate the pattern of each individual element. This treatment allows the element responses to be directly involved in the weight adjustment algorithm and contribute to the array overall response without having any additional complexity. The proposed method can handle different types of the constraints, although the analysis presented here is based on the angle–frequency domain constraints which nevertheless eliminates the presence of the pre-steering delays and ensures a frequency invariant beampatterm required for wideband beamforming. The simulation results which are presented for a typical cylindrical array show that the proposed method can create the desired broadband beampattern with high performance and in an adaptive manner.

Generalized sidelobe canceler beamforming applied to medical ultrasound imaging

A generalized sidelobe canceler (GSC) approach is proposed for medical ultrasound imaging. The approach uses a set of adaptive weights instead of traditional non-adaptive weights, thus suppressing the interference and noise signal of echo data. In order to verify the validity of the proposed approach, Field II is applied to obtain the echo data of synthetic aperture (SA) for 13 scattering points and circular cysts. The performance of GSC is compared with SA using boxcar weights and Hamming weights, and is quantified by the full width at half maximum (FWHM) and peak signal-to-noise ratio (PSNR). Imaging of scattering point utilizing SA, SA (hamming), GSC provides FWHMs of 1.13411, 1.68910, 0.36195 mm and PSNRs of 60.65, 57.51, 66.72 dB, respectively. The simulation results of circular cyst also show that GSC can perform better lateral resolution than non-adaptive beamformers. Finally, an experiment is conducted on the basis of actual echo data of an ultrasound system, the imaging result after SA, SA (hamming), GSC provides PWHMs of 2.55778, 3.66776, 1.01346 mm at z = 75.6 mm, and 2.65430, 3.76428, 1.27889 mm at z = 77.3 mm, respectively.

Generalized sidelobe canceller beamforming method for ultrasound imaging.

A modified generalized sidelobe canceller (IGSC) algorithm is proposed to enhance the resolution and robustness against the noise of the traditional generalized sidelobe canceller (GSC) and coherence factor combined method (GSC-CF). In the GSC algorithm, weighting vector is divided into adaptive and non-adaptive parts, while the non-adaptive part does not block all the desired signal. A modified steer vector of the IGSC algorithm is generated by the projection of the non-adaptive vector on the signal space constructed by the covariance matrix of received data. The blocking matrix is generated based on the orthogonal complementary space of the modified steer vector and the weighting vector is updated subsequently. The performance of IGSC was investigated by simulations and experiments. Through simulations, IGSC outperformed GSC-CF in terms of spatial resolution by 0.1 mm regardless there is noise or not, as well as the contrast ratio respect. The proposed IGSC can be further improved by combining with CF. The experimental results also validated the effectiveness of the proposed algorithm with dataset provided by the University of Michigan.

Adaptive Widely Linear Constrained Constant Modulus Reduced-Rank Beamforming

We propose a blind adaptive reduced-rank widely linear beamforming algorithm using the generalized sidelobe canceller structure for interference suppression. A structured Krylov-subspace-based approach is devised to construct the dimensionality reducing transformation matrix, and a recursive least-squares algorithm is developed according to the widely linear constrained constant modulus criterion to update the reduced-rank filter. We analyze the convergence and complexity of the proposed algorithm and validate its performance gains through simulations.

Suppression of Mutual Interference in Noncontiguous Orthogonal Frequency Division Multiplexing Based Cognitive Radio Systems

Orthogonal frequency division multiplexing (OFDM) is a favourable technology for dynamic spectrum access (DSA) due to the flexibility in spectrum shaping. In spite of that, high sidelobes of OFDM subcarriers bring in considerable interference to the nearby users, particularly in OFDM based cognitive radio (CR) networks, where the secondary users (SUs) are capable of accessing the spectrum opportunistically. In this paper, two new techniques for the suppression of high sidelobes are proposed. The proposed techniques composed of an optimization scheme are followed by generalized sidelobe canceller. The proposed techniques can be considered as a two-level suppression technique in the sense that in the first level the sidelobe is reduced by using cancellation carriers (CCs), whose amplitudes are determined using genetic algorithm (GA) and differential evolution (DE), while in the second level further reduction of sidelobe is achieved using generalized sidelobe canceller (GSC). Simulation results show the power spectral density (PSD) performance of the proposed techniques in comparison with already existing techniques, demonstrating that the proposed techniques minimize the out-of-band radiation (OOBR) significantly, thus qualifying for more effective spectrum sharing.

New Generalized Sidelobe Canceller with Denoising Auto-Encoder for Improved Speech Enhancement

New Generalized Sidelobe Canceller with Denoising Auto-Encoder for Improved Speech Enhancement

Performance Analysis of the Generalized Sidelobe Canceller in Finite Sample Size and Correlative Interference Situations

Performance Analysis of the Generalized Sidelobe Canceller in Finite Sample Size and Correlative Interference Situations

Forward-backward generalized sidelobe canceler beamforming applied to medical ultrasound imaging

For adaptive ultrasound imaging, accurate estimation of the covariance matrix is of great importance, and it has a fundamental influence on the performance of the adaptive beamformer. In this paper, a new forward-backward generalized sidelobe canceler (FBGSC) approach is proposed for medical ultrasound imaging, which uses forward and backward subaperture averaging to accurate estimate the covariance matrix. And resulted from accurate estimating of covariance matrix, FBGSC can achieve better lateral resolution and contrast without preprocessing algorithms. Field II is applied to obtain the simulated echo data of scattering points and a circular cyst. Beamforming responses of scattering points show that FBGSC can improve the lateral resolution by 55.7% and 66.6% compared with synthetic aperture (SA) and delay-and-sum (DS), respectively. Similarly, the simulated results of circular cyst show that FBGSC can obtain better beamforming responses than traditional adaptive beamformers. Finally, an experiment is conducted based on the real echo data of a medical ultrasound system. Results demonstrate that the FBGSC can improve the imaging quality of medical ultrasound imaging system, with lower computational demand and higher reliability.

Generalised reduced-rank structure for broadband space–time GSC and its fast algorithm

Space–time generalised sidelobe canceller (GSC) is a well-substantiated method for broadband beamforming. In this paper, a generalised reduced-rank structure is established for the broadband space–time GSC. The generalised structure estimates signal subspace by a reduced-rank transform matrix, and so the dimension of broadband signal data vector is decreased. Therefore, the computational complexity for obtaining the adaptive weights is reduced. Generally, the reduced-rank matrix is obtained by eigen-decomposition of the data covariance matrix, which is a large computational load for broadband space–time processing. A fast reduced-rank algorithm is then proposed for the generalised structure to rapidly construct the reduced-rank matrix and to alleviate the computational burden caused by eigen-decomposition. The signal subspace is rather robust to the received data, hence, a set of received data can be used to construct the reduced-rank matrix for a rough and fast estimate of the signal subspace. With the undistorted response to signals of interest and the satisfactory anti-interference capability, the proposed algorithm could effectively reduce the computational complexity of the adaptive weight approach. Simulation results highlight the correctness and effectiveness of the proposed methods.

일반화된 부엽 제거기 기반 시역전 기술을 이용한 수중음향통신 성능 분석

수중음향통신에서 다중 입출력(Multiple-Input-Multiple-Output, MIMO) 환경은 인접 심볼 간 간섭뿐만아니라 송신기 간의 채널 간 간섭의 영향으로 인하여 수신 신호의 왜곡이 발생하는 특징을 갖는다. 신호 보상을 위하여 시역전 기술이 이용되었지만 기존의 시역전 기술은 채널 간 간섭을 효과적으로 제거하지 못하는 한계가 있다. 본 논문에서는 채널간 간섭의 제거를 위해 일반화된 부엽 제거기(Generalized Sidelobe Canceller, GSC)를 적용한 시역전 기술을 제안한다. 제안된 방법의 검증을 위해 FAF05(The Focused Acoustic Forecasting 05) 해상 실험 데이터를 이용하여 기존의 시역전 기술과의 통신 성능 비교를 수행하였으며, 그 결과 제안된 방법에 대한 통신 성능이 기존의 시역전 기술에 비해 향상됨을 확인 할 수 있었다. MIMO (Multiple-Input-Multiple-Output) in underwater acoustic communication has distortion of received signal because of ISI (Inter-Symbol Interference) and crosstalk among transmitters. Time-reversal mirror was used for compensating of signal distortion, but it has a limit in eliminating crosstalk effectively. This paper proposes a time-reversal mirror based on GSC (Generalized Sidelobe Canceller) for removing crosstalk. The FAF05 (The Focused Acoustic Forecasting 05) experimental data has been used to verify the suggested method by comparison with the conventional time-reversal for communication performance, and it is demonstrated that the suggested method produces better communication performance results than conventional time-reversal.

Techniques for the suppression of sidelobes in a non-contiguous orthogonal frequency division multiplexing framework

In orthogonal frequency division multiplexing (OFDM)-based cognitive radio (CR) systems, high out-of-band radiation (OOBR) results in severe interference to the neighboring users, including licensed users (LUs) and cognitive radio users (CRUs). To tackle that issue, a framework of non-contiguous orthogonal frequency division multiplexing (NCOFDM) is presented in this paper that has the ability of describing any OOBR reduction techniques, regardless of whether a single or multiple techniques are applied. Based on this framework, we proposed four new different schemes that can be viewed as two-level suppression schemes. In the first level, the OOBR is reduced by techniques represented by precoding matrices, while in the second level further reduction of OOBR is done by using generalized sidelobe canceller (GSC). Numerical results show that the proposed schemes can suppress the OOBR significantly in terms of power spectral density (PSD), thus allowing the successful coexistence of LUs, as well as CRUs in a spectrum-sharing environment.

Finite data performance analysis of a sidelobe canceller

The performance of the generalized sidelobe canceller (GSC) is affected by the desired signal (DS) even if all signals are uncorrelated with each other when the DS exists in the received array data with finite snapshot number. Under the condition that the DS is blocked totally in the auxiliary array, a novel expression of the weight vector of the GSC, where the auxiliary array is separated from the main array, is derived for the finite data. Based on the new weight vector, the corresponding expressions of the output signal-to-interference-plus-noise ratio (SINR) can be developed for the case that all signals, including the DS and interference signals, are independent with each other. Then, effects on the SINR for some parameters, including the signal-to-noise ratio, the array antenna number, the direction-of-arrival of the interference signal and the interference-to-noise ratio, are studied, respectively. Some guidelines can thus be obtained for the practical application.

Eigenspace-Based Generalized Sidelobe Canceler Beamforming Applied to Medical Ultrasound Imaging.

The use of a generalized sidelobe canceler (GSC) can significantly improve the lateral resolution of medical ultrasound systems, but the contrast improvement isn’t satisfactory. Thus a new Eigenspace-based generalized sidelobe canceler (EBGSC) approach is proposed for medical ultrasound imaging, which can improve both the lateral resolution and contrast of the system. The weight vector of the EBGSC is obtained by projecting the GSC weight vector onto a vector subspace constructed from the eigenstructure of the covariance matrix, and using the new weight vector instead of the GSC ones leads to reduced sidelobe level and improved contrast. Simulated and experimental data are used to evaluate the performance of the proposed method. The Field II software is applied to obtain the simulated echo data of scattering points and circular cysts. Imaging of scattering points show that EBGSC has the same full width at half maximum (FWHM) as GSC, while the lateral resolution improves by 35.3% and 52.7% compared with synthetic aperture (SA) and delay-and-sum (DS), respectively. Compared with GSC, SA and DS, EBGSC improves the peak sidelobe level (PSL) by 23.55, 33.11 and 50.38 dB, respectively. Also the cyst contrast increase by EBGSC was calculated as 16.77, 12.43 and 26.73 dB, when compared with GSC, SA and DS, respectively. Finally, an experiment is conducted on the basis of the complete echo data collected by a medical ultrasonic imaging system. Results show that the proposed method can produce better lateral resolution and contrast than non-adaptive beamformers.

Constrained Spectral Conditioning for spatial sound level estimation

Microphone arrays are utilized in aeroacoustic testing to spatially map the sound emitted from an article under study. Whereas a single microphone allows only the total sound level to be estimated at the measurement location, an array permits differentiation between the contributions of distinct components. The accuracy of these spatial sound estimates produced by post-processing the array outputs is continuously being improved. One way of increasing the estimation accuracy is to filter the array outputs before they become inputs to a post-processor. This work presents a constrained method of linear filtering for microphone arrays which minimizes the total signal present on the array channels while preserving the signal from a targeted spatial location. Thus, each single-channel, filtered output for a given targeted location estimates only the signal from that location, even when multiple and/or distributed sources have been measured simultaneously. The method is based on Conditioned Spectral Analysis and modifies the Wiener–Hopf equation in a manner similar to the Generalized Sidelobe Canceller. This modified form of Conditioned Spectral Analysis is embedded within an iterative loop and termed Constrained Spectral Conditioning. Linear constraints are derived which prevent the cancellation of targeted signal due to random statistical error as well as location error in the sensor and/or source positions. The increased spatial mapping accuracy of Constrained Spectral Conditioning is shown for a simulated dataset of point sources which vary in strength. An experimental point source is used to validate the efficacy of the constraints which yield preservation of the targeted signal at the expense of reduced filtering ability. The beamforming results of a cold, supersonic jet demonstrate the qualitative and quantitative improvement obtained when using this technique to map a spatially-distributed, complex, and possibly coherent sound source.

A robust generalized sidelobe canceller via steering vector estimation

In the presence of the direction of arrival (DOA) mismatch, the performance of generalized sidelobe canceller (GSC) may suffer severe degradation due to the gain loss of the desired signal in the main array and cancellation. In this paper, one effective GSC algorithm is proposed to improve the robustness against the DOA mismatch of the desired signal. Firstly, two subspaces, which contain the desired signal’s actual steering vectors of the main and auxiliary arrays, can be obtained by using the range information of the angle which the desired signal may come from. By rotating these two subspaces, the desired signal’s actual steering vectors of the main and auxiliary arrays can be estimated based on the maximum output power criterion. Then, with the estimates of the steering vectors in the former step, the gain loss of the desired signal in the main array can be alleviated. Moreover, one adaptive weight vector with the ability to block the desired signal in the auxiliary array can be obtained simultaneously, which effectively avoids the signal of interest cancellation consequently. Cycle iterative approach is also applied to guarantee the estimation accuracy of a wide range of angle deviation. Numerical simulations demonstrate the effectiveness and applicability of the proposed method.