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Integrated polarisation and diversity smoothing algorithm for DOD and DOA estimation of coherent targets

IET signal PROCESSING 2018年第4期12卷 447-453页

作者： Chintagunta, Srinivasarao Ponnusamy, Palanisamy Natl Inst Technol Dept Elect & Commun Engn Tiruchirappalli 620015 Tamil Nadu India

This study proposes a novel integrated polarisation and diversity smoothing (IPDS) algorithm to solve the direction estimation problem of coherent targets in bistatic multiple-input multiple-output (MIMO) radar with electromagnetic vector sensors (EVSs). The IPDS algorithm partitions the transmit and receive arrays into multiple subarrays based on the sensor elements and the spatial phase shift factors. Then the covariance matrices of the received signals from coherent targets associated with these subarrays are smoothened to restore the rank inadequacy of the reflection coefficient covariance matrix. After applying the IPDS algorithm, the direction of departure (DOD) and the direction of arrival (DOA) are estimated using the estimation of signal parameters via rotational invariance technique and the multiple signal classification methods. The effectiveness of the proposed algorithm in terms of decorrelation factor, estimation accuracy, precision and the spatial spectrum is evaluated through computer simulations. Cramer-Rao lower bound is derived for the bistatic MIMO radar with EVSs to substantiate the proposed algorithm. The simulation results are compared with the diversity smoothing and the polarisation smoothing algorithms available in literature. The results obtained by using the proposed algorithm were found to be impressive.

关键词： radar signal processing signal classification array signal processing direction-of-arrival estimation MIMO radar diversity reception electromagnetic wave polarisation smoothing methods covariance matrices decorrelation integrated polarisation-and-diversity smoothing algorithm IPDS algorithm DOD estimation DOA estimation coherent targets direction estimation problem bistatic multiple-input multiple-output radar bistatic MIMO radar electromagnetic vector sensors EVS transmit arrays receive arrays sensor elements spatial phase shift factors multiple subarrays covariance matrices reflection coefficient covariance matrix direction-of-departure estimation direction-of-arrival estimation signal parameters estimation rotational invariance technique multiple signal classification methods decorrelation factor estimation accuracy spatial spectrum computer simulations Cramer-Rao lower bound

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Multivariate signal parameter estimation under dependent noise from 1-Bit dithered quantized data

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IEEE TRANSACTIONS ON INFORMATION THEORY 2008年第4期54卷 1637-1654页

作者： Dabeer, Onkar Masry, Elias Tata Inst Fundamental Res Sch Technol & Comp Sci Bombay 400005 Maharashtra India Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

Motivated by applications in sensor networks and communications, we consider multivariate signal parameter estimation when only dithered 1-bit quantized samples are available. The observation noise is taken to be a stationary, strongly mixing process, which covers a wide range of processes including autoregressive moving average (ARMA) models. The noise is allowed to be Gaussian or to have a heavy-tail (with possibly infinite variance). An estimate of the signal parameters is proposed and is shown to be weakly consistent. Joint asymptotic normality of the parameters estimate is also established and the asymptotic mean and covariance matrices are identified.

关键词： 1-bit dithered quantization dependent data sensor networks signal parameters estimation

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High-resolution velocity-azimuth joint estimation for random-time-division-multiplexing multiple-input-multiple-output automotive radar using matrix completion

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IET RADAR SONAR AND NAVIGATION 2021年第10期15卷 1281-1296页

作者： Hu, Xueyao Zhang, Liang Long, Jiamin Liang, Can Liu, Jianhu Wang, Yanhua Beijing Inst Technol Sch Informat & Elect Radar Res Lab Beijing 100081 Peoples R China Chongqing Innovat Ctr Beijing Inst Technol Chongqing 401120 Peoples R China Beijing Key Lab Embedded Real Time Informat Proc Beijing Peoples R China Beijing Rxbit Elect Technol Co Ltd Beijing Peoples R China

Due to its low hardware complexity, small volume and simple structure, time-division-multiplexing multiple-input-multiple-output (TDM MIMO) radar has been widely applied in automotive applications. The transmitting antennas of TDM MIMO automotive radar are usually switched according to a sequential-TDM pattern. However, moving targets can introduce a motion-induced phase into the sequential-TDM pattern, which is coupled to the spatial phase, resulting in errors in velocity and azimuth estimation. Herein, a random-TDM pattern with the matrix completion (MC)-based estimation method is proposed to address these issues. In the proposed method, the random-TDM pattern, which means randomly activating the transmitting antenna instead of sequentially, can decouple the linear temporal-spatial coupling phase, avoiding the coupling problem in velocity and azimuth estimation. Then, by reshaping the echo data into a matrix form of sparse sampling, the inexact augmented Lagrange multiplier algorithm is adopted to recover this matrix, solving the underdetermined estimation problem caused by sparse sampling. Finally, the high-accuracy velocity and azimuth can be jointly estimated by applying the estimation of signal parameters via rotational invariance technique algorithm to the recovered full sampling data. Moreover, compared with the compressed sensing-based method, the proposed method overcomes the grid mismatch problem. The results of comparative simulations and real-data experiments demonstrate the feasibility of the proposed method.

关键词： radar signal processing Radar theory full sampling data rotational invariance technique algorithm Communication switching matrix form inexact augmented Lagrange multiplier algorithm echo data velocity estimation Linear algebra (numerical analysis) multiple-input-multiple-output automotive radar Optimisation techniques signal parameters estimation signal processing and detection coupling problem randomly activated transmitting antennas random-time-division-multiplexing automotive radar optimisation matrix algebra Other topics in statistics sparse sampling Radar equipment, systems and applications velocity measurement Automobile electronics Velocity, acceleration and rotation measurement transmitting antennas road vehicle radar matrix completion-based estimation method linear temporal-spatial coupling phase estimation theory azimuth estimation Antenna arrays random-TDM pattern array signal processing grid mismatch problem time division multiplexing radar antennas TDM MIMO radar high-resolution velocity-azimuth joint estimation MIMO radar underdetermined estimation problem

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Super-resolution algorithm for instantaneous ISAR imaging

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ELECTRONICS LETTERS 2000年第3期36卷 253-255页

作者： Sun, CY Bao, Z Xidian Univ Key Lab Radar Signal Proc Xian 710071 Peoples R China

The super resolution method is investigated for use in instantaneous inverse synthetic aperture radar (ISAR) imaging. The time-varying Doppler spectrum is modelled as that of superimposed LFM chirp signals in a short time interval. A parametric relaxation-based algorithm is proposed for estimating the parameters of the signals. The effectiveness of the algorithm is verified by applying it to ISAR imaging.

关键词： signal parameters estimation Doppler effect superimposed LFM chirp signals military radar synthetic aperture radar imaging inverse SAR imaging Military radar, detection and tracking systems Optical, image and video signal processing parameter estimation time-varying Doppler spectrum modelling radar imaging Radar theory spectral analysis image resolution instantaneous ISAR imaging synthetic aperture radar super-resolution algorithm parametric relaxation-based algorithm

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Em algorithm applied to non-stationary noisy phase signals

Em algorithm applied to non-stationary noisy phase signals

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IEEE International Conference on Acoustics, Speech, and signal Processing

作者： Taleb, A Ericsson Radio Syst AB SE-16480 Stockholm Sweden

ISBN: (纸本)0780374029

This paper concerns the application of the EM algorithm for the estimation of the parameters of non-stationary noisy phase mono component signals buried in additive noise. Noisy phase signals are appropriate for modeling real world signals such as radar and communications signals. The maximum likelihood estimator for the signal parameters is explicited. The problem is then formulated as a missing data problem which enables a natural use of the Expectation-Maximization algorithm. A robust initialization scheme based on non-parametric time-frequency distributions is presented. Experimental results with both real and simulated data show the efficiency of the procedure.

关键词： optimisation maximum likelihood estimation noise time-frequency analysis statistical analysis signal processing frequency modulation EM algorithm nonstationary noisy phase signals expectation maximization algorithm parameter estimation noisy phase mono component signals additive noise radar signals communications signals maximum likelihood estimator MLE signal parameters estimation missing data problem robust initialization nonparametric time-frequency distributions quadratic FM signal amplitude modulation AM simulated data real data

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High-resolution phased array signal processing via DFT Beamspace TLS-ESPRIT with structure weighting 6

High-resolution phased array signal processing via DFT Beams...

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IEEE International Symposium on Phased Array Systems and Technology

作者： Vasylyshyn, VI Kharkov Air Force Inst UA-61165 Kharkov Ukraine

ISBN: (纸本)078037827X

A new algorithm, DFT Beamspace TLS-ESPRIT with structure weighting is presented. The proposed algorithm provides closed-form estimates of the directions-of-arrival (DOAs) of signals impinging on a Uniform Linear Array (ULA). DFT Beamspace TLS-ESPRIT with structure weighting outperforms DFT Beamspace TLS-ESPRIT in terms of estimation accuracy, mainly at small and mean values of SNR, and conserves the low computational complexity of the latter algorithm. Improvement of performance is conditioned by exploiting structure (row) weighting method. Distinctions in realization of structure weighting in beamspace as compared to element space are noted. The performance of the proposed algorithm is evaluated by computer simulation, verifying its statistical efficiency.

关键词： direction-of-arrival estimation computational complexity invariance discrete Fourier transforms array signal processing signal resolution structure weighting TLS-ESPRIT DFT beamspace phased array signal processing directions-of-arrival estimation uniform linear array signal parameters estimation discrete Fourier transform rotational invariance techniques

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The Time Difference of Arrival estimation of Wi-Fi signals

The Time Difference of Arrival Estimation of Wi-Fi Signals

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作者： Nemec, Z. Brno University of Technology

The papers deals with a modeling of a Time- Difference of Arrival system for a subscriber station localization, based on the 802.11 standard wireless network. In the case of severe multipath effects the standard TDOA estimation methods, based on correlation of signals, received by conveniently displaced receiving stations show large errors. Thus, a new algorithm is proposed using received signals decomposition to a set of delayed replicas. This represents a linear estimation of reflected signals amplitudes. The described method leads to a better estimation of time differences of the signals, propagating on the direct paths between the emitter and the receiving stations.

关键词： Positioning multipath propagation correlated signals wall reflections signal parameters estimation signal processing

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