Space-Time Adaptive Processing Based on Jointly Sensing of Multiple Measurements
FANG Ming1, DAI Feng-zhou1, LIU Hong-wei1, WANG Xiao-mo1,2
1. National Laboratory of Radar Signal Processing, Xidian University, Xi'an, Shaanxi 710071, China;
2. China Academy of Electronics and Information Technology, Beijing 100041, China
Space-time adaptive processing (STAP) is widely used for clutter mitigation in airborne radar.However,STAP shows significantly performance degradation for lacking sufficient independent identically distributed (IID) training samples in heterogeneous environment.To solve this problem,we propose a STAP approach based on jointly sensing of multiple measurements.The method sets the radar work with orthogonal and identical waveforms alternately,and achieves the clutter information by current and previous environment echoes.Then the clutter information and platform parameters are used,and a clutter covariance matrix is obtained incorporating system parameters.Finally the space-time processor can be built based on the combination of the estimated clutter covariance matrix and the sample covariance matrix.The simulation results show that the new approach can achieve better clutter mitigation performance under the circumstance of inaccurate environmental knowledge.
方明, 戴奉周, 刘宏伟, 王小谟. 基于多帧观测联合感知的空时自适应处理[J]. 电子学报, 2015, 43(12): 2368-2373.
FANG Ming, DAI Feng-zhou, LIU Hong-wei, WANG Xiao-mo. Space-Time Adaptive Processing Based on Jointly Sensing of Multiple Measurements. Chinese Journal of Electronics, 2015, 43(12): 2368-2373.
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2015, Vol. 43 
