This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter mod...This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter model,STAP performance is then analyzed from the perspective of covariance matrix tapering（CMT）.For STAP performance degradation due to array rotation,a determinate compensation method is proposed based on the CMT method.Numerical examples are provided to verify the analysis and the proposed compensation method.展开更多
Adaptive antenna arrays have been used to mitigate the interference on global navigation satellite system（GNSS） receivers. The performance of interference mitigation depends on the beamforming algorithms adopted by ...Adaptive antenna arrays have been used to mitigate the interference on global navigation satellite system（GNSS） receivers. The performance of interference mitigation depends on the beamforming algorithms adopted by the antenna array. However,the adaptive beamforming will change the array pattern in realtime, which has the potential to introduce phase center biases into the antenna array. For precise applications, these phase biases must be mitigated or compensated because they will bring errors in code phase and carrier phase measurements. A novel adaptive beamforming algorithm is proposed firstly, then the phase bias induced by the proposed algorithm is estimated, and finally a compensation strategy is addressed. Simulations demonstrate that the proposed beamforming algorithm suppresses effectively the strong interference and improves significantly the capturing performance of GNSS signals. Simultaneously, the bias compensation method avoids the loss of the carrier phase lock and reduces the phase measurement errors for GNSS receivers.展开更多
The derivation of a diagonally loaded sample-matrix inversion （LSMI） algorithm on the busis of inverse matrix recursion （i.e.LSMI-IMR algorithm） is conducted by reconstructing the recursive formulation of covarian...The derivation of a diagonally loaded sample-matrix inversion （LSMI） algorithm on the busis of inverse matrix recursion （i.e.LSMI-IMR algorithm） is conducted by reconstructing the recursive formulation of covariance matrix. For the new algorithm, diagonal loading is by setting initial inverse matrix without any addition of computation. In addition, a corresponding improved recursive algorithm is presented, which is low computational complexity. This eliminates the complex multiplications of the scalar coefficient and updating matrix, resulting in significant computational savings. Simulations show that the LSMI-IMR algorithm is valid.展开更多
In this paper,a space-time adaptive processing(STAP)method is proposed for the airborne radar with the array amplitude-phase error considered,which is based on atomic norm minimization(ANM).In the conventional ANM-bas...In this paper,a space-time adaptive processing(STAP)method is proposed for the airborne radar with the array amplitude-phase error considered,which is based on atomic norm minimization(ANM).In the conventional ANM-based STAP method,the influence of the array amplitude-phase error is not considered and restrained,which inevitably causes performance deterioration.To solve this problem,the array amplitude-phase error is firstly estimated.Then,by pre-estimating the array amplitude-phase error information,a modified ANM model is built,in which the array amplitude-phase error factor is separated from the clutter response and the clutter covariance matrix(CCM)to improve the estimation accuracy of the CCM.To prove that the atomic norm theory is applicable in the presence of the array amplitude-phase error,the clutter sparsity is analyzed in this paper.Meanwhile,simulation results demonstrate that the proposed method is superior to the state-of-the-art STAP method.Moreover,the measured data is used to verify the effectiveness of the proposed method.展开更多
Space-time adaptive processing（STAP） has been proven to be one of the best techniques capable of detecting weak moving targets in strong clutter environment and has been widely applied in airborne ground moving targ...Space-time adaptive processing（STAP） has been proven to be one of the best techniques capable of detecting weak moving targets in strong clutter environment and has been widely applied in airborne ground moving target indication（GMTI） radar.This paper applies an amplitude and phase estimation（APES） approach to two aspects of the STAP algorithm.Firstly,APES is applied to accurately describe the clutter characteristic in angle-Doppler domain.Then,APES is incorporated into the standard STAP algorithm to improve its performance without increasing transmitting/receiving channel and pulse number.The experimental examples show that the detection performance can be improved by using the APES technique,as well as the high computational complexity can be avoided.展开更多
A new two-stage reduced-dimension space-time adaptiveprocessing （STAP） approach, which combines the subcoherentprocessing interval （sub-CPI） STAP and the principalcomponent analysis （PCA）, is proposed to achieve...A new two-stage reduced-dimension space-time adaptiveprocessing （STAP） approach, which combines the subcoherentprocessing interval （sub-CPI） STAP and the principalcomponent analysis （PCA）, is proposed to achieve a more enhancedconvergence measure of effectiveness （MOE）. Furthermore,in the case of the subspace leakage phenomenon, theproposed STAP method is modified to hold the fast convergenceMOE by using the covariance matrix taper （CMT） technique. Bothsimulation and real airborne radar data processing are providedto analyze the convergence MOE performance of the proposedSTAP methods. The results show the proposed method is moresuitable for the practical radar applications when compared withthe conventional sub-CPI STAP method.展开更多
基金supported by the National Natural Science Foundation of China(60901056)
文摘This paper proposes a unified clutter model incorporating the effects of range walk and array rotation for space-time adaptive processing（STAP） in airborne multi-channel early-warning radar.Based on this clutter model,STAP performance is then analyzed from the perspective of covariance matrix tapering（CMT）.For STAP performance degradation due to array rotation,a determinate compensation method is proposed based on the CMT method.Numerical examples are provided to verify the analysis and the proposed compensation method.
基金supported by the National Natural Science Foundation of China(61301094)the Postdoctoral Science Foundation of China(2014M552490)
文摘Adaptive antenna arrays have been used to mitigate the interference on global navigation satellite system（GNSS） receivers. The performance of interference mitigation depends on the beamforming algorithms adopted by the antenna array. However,the adaptive beamforming will change the array pattern in realtime, which has the potential to introduce phase center biases into the antenna array. For precise applications, these phase biases must be mitigated or compensated because they will bring errors in code phase and carrier phase measurements. A novel adaptive beamforming algorithm is proposed firstly, then the phase bias induced by the proposed algorithm is estimated, and finally a compensation strategy is addressed. Simulations demonstrate that the proposed beamforming algorithm suppresses effectively the strong interference and improves significantly the capturing performance of GNSS signals. Simultaneously, the bias compensation method avoids the loss of the carrier phase lock and reduces the phase measurement errors for GNSS receivers.
文摘The derivation of a diagonally loaded sample-matrix inversion （LSMI） algorithm on the busis of inverse matrix recursion （i.e.LSMI-IMR algorithm） is conducted by reconstructing the recursive formulation of covariance matrix. For the new algorithm, diagonal loading is by setting initial inverse matrix without any addition of computation. In addition, a corresponding improved recursive algorithm is presented, which is low computational complexity. This eliminates the complex multiplications of the scalar coefficient and updating matrix, resulting in significant computational savings. Simulations show that the LSMI-IMR algorithm is valid.
基金supported by the Fund for Foreign Scholars in University Research and Teaching Programs(the 111 Project)(B18039)。
文摘In this paper,a space-time adaptive processing(STAP)method is proposed for the airborne radar with the array amplitude-phase error considered,which is based on atomic norm minimization(ANM).In the conventional ANM-based STAP method,the influence of the array amplitude-phase error is not considered and restrained,which inevitably causes performance deterioration.To solve this problem,the array amplitude-phase error is firstly estimated.Then,by pre-estimating the array amplitude-phase error information,a modified ANM model is built,in which the array amplitude-phase error factor is separated from the clutter response and the clutter covariance matrix(CCM)to improve the estimation accuracy of the CCM.To prove that the atomic norm theory is applicable in the presence of the array amplitude-phase error,the clutter sparsity is analyzed in this paper.Meanwhile,simulation results demonstrate that the proposed method is superior to the state-of-the-art STAP method.Moreover,the measured data is used to verify the effectiveness of the proposed method.
文摘Space-time adaptive processing（STAP） has been proven to be one of the best techniques capable of detecting weak moving targets in strong clutter environment and has been widely applied in airborne ground moving target indication（GMTI） radar.This paper applies an amplitude and phase estimation（APES） approach to two aspects of the STAP algorithm.Firstly,APES is applied to accurately describe the clutter characteristic in angle-Doppler domain.Then,APES is incorporated into the standard STAP algorithm to improve its performance without increasing transmitting/receiving channel and pulse number.The experimental examples show that the detection performance can be improved by using the APES technique,as well as the high computational complexity can be avoided.
基金supported by the National Natural Science Foundation of China(611011296122700161301089)
文摘A new two-stage reduced-dimension space-time adaptiveprocessing （STAP） approach, which combines the subcoherentprocessing interval （sub-CPI） STAP and the principalcomponent analysis （PCA）, is proposed to achieve a more enhancedconvergence measure of effectiveness （MOE）. Furthermore,in the case of the subspace leakage phenomenon, theproposed STAP method is modified to hold the fast convergenceMOE by using the covariance matrix taper （CMT） technique. Bothsimulation and real airborne radar data processing are providedto analyze the convergence MOE performance of the proposedSTAP methods. The results show the proposed method is moresuitable for the practical radar applications when compared withthe conventional sub-CPI STAP method.
