For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in ...For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion finding.The results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse noise.Other than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.展开更多
This paper derives the extended ambiguity function for a bistatic multiple-input multiple-output (MIMO) radar system, which includes the whole radar system parameters: geometric sensor configuration, waveforms, ran...This paper derives the extended ambiguity function for a bistatic multiple-input multiple-output (MIMO) radar system, which includes the whole radar system parameters: geometric sensor configuration, waveforms, range, range rate, target scattering and noise characteristics. Recent research indicates the potential pa- rameter estimate performance of bistatic MIMO radars. And this ambiguity function can be used to analyze the parameter estimate performance for the relationship with the Cramer-Rao bounds of the estimated parameters. Finally, some examples are given to demonstrate the good parameter estimate performance of the bistatic MIMO radar, using the quasi-orthogonal waveforms based on Lorenz chaotic systems.展开更多
A decoupling-estimation signal parameters via rotarional invariance technique(ESPRIT) method is presented for multi-target localization with unknown mutual coupling in bistatic multiple-input multiple-output(MIMO)...A decoupling-estimation signal parameters via rotarional invariance technique(ESPRIT) method is presented for multi-target localization with unknown mutual coupling in bistatic multiple-input multiple-output(MIMO) radar.Two steps are carried out in this method.The decoupling operation between angle and mutual coupling estimates is realized by choosing the auxiliary elements on both sides of the transmit and receive uniform linear arrays(ULAs).Then the ESPRIT method is resilient against the unknown mutual coupling matrix(MCM) and can be directly utilized to estimate the direction of departure(DOD) and the direction of arrival(DOA).Moreover,the mutual coupling coefficient is estimated by finding the solution of the linear constrained optimization problem.The proposed method allows an efficient DOD and DOA estimates with automatic pairing.Simulation results are presented to verify the effectiveness of the proposed method.展开更多
基金This work was supported by the National Natural Science Foundation of China(62073093)the Postdoctoral Scientific Research Developmental Fund of Heilongjiang Province(LBH-Q19098)+1 种基金the Heilongjiang Provincial Natural Science Foundation of China(LH2020F017)the Key Laboratory of Advanced Marine Communication and Information Technology,Ministry of Industry and Information Technology.
文摘For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise environment.By means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion finding.The results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse noise.Other than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.
基金supported by the Innovation Project for Excellent Postgraduates of Hunan Province (CX2011B018)the Innovation Project for Excellent Postgraduates of National University of Defense Technology (B110402)
文摘This paper derives the extended ambiguity function for a bistatic multiple-input multiple-output (MIMO) radar system, which includes the whole radar system parameters: geometric sensor configuration, waveforms, range, range rate, target scattering and noise characteristics. Recent research indicates the potential pa- rameter estimate performance of bistatic MIMO radars. And this ambiguity function can be used to analyze the parameter estimate performance for the relationship with the Cramer-Rao bounds of the estimated parameters. Finally, some examples are given to demonstrate the good parameter estimate performance of the bistatic MIMO radar, using the quasi-orthogonal waveforms based on Lorenz chaotic systems.
基金supported by the National Natural Science Foundation of China (60702015)
文摘A decoupling-estimation signal parameters via rotarional invariance technique(ESPRIT) method is presented for multi-target localization with unknown mutual coupling in bistatic multiple-input multiple-output(MIMO) radar.Two steps are carried out in this method.The decoupling operation between angle and mutual coupling estimates is realized by choosing the auxiliary elements on both sides of the transmit and receive uniform linear arrays(ULAs).Then the ESPRIT method is resilient against the unknown mutual coupling matrix(MCM) and can be directly utilized to estimate the direction of departure(DOD) and the direction of arrival(DOA).Moreover,the mutual coupling coefficient is estimated by finding the solution of the linear constrained optimization problem.The proposed method allows an efficient DOD and DOA estimates with automatic pairing.Simulation results are presented to verify the effectiveness of the proposed method.