National Natural Science Foundation of China (No.61201285, No.61271291);Program for New Century Excellent Talents in University of Ministry of Education of China (No.NCET-09-0630);Foundation for the Author of National Excellent Doctoral Dissertation of PR China (No.FANEDD-201156)
FANG Ming, DAI Feng-zhou, LIU Hong-wei, et al. Space-Time Adaptive Processing Based on Jointly Sensing of Multiple Measurements[J]. Acta Electronica Sinica, 2015, 43(12): 2368-2373.
DOI:
FANG Ming, DAI Feng-zhou, LIU Hong-wei, et al. Space-Time Adaptive Processing Based on Jointly Sensing of Multiple Measurements[J]. Acta Electronica Sinica, 2015, 43(12): 2368-2373. DOI: 10.3969/j.issn.0372-2112.2015.12.004.
Space-Time Adaptive Processing Based on Jointly Sensing of Multiple Measurements
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.