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.