时变环境下RCS测量中的精确背景抵消处理技术

In outdoor radar cross section (RCS) measurement, background clutter cannot be suppressed effectively using conventional background subtraction technique due to the fact that, influenced by time-variant outdoor environment, the amplitudes and phases of radar received returns collected at different time interval are not perfectly coherent. A parametric model is developed to characterize the effect of such a time-variant environment on radar received returns. Meanwhile, a technique for improved exact background subtraction is proposed based on the parametric model. First, the return data of specified region with an ancillary reference signal available is extracted from the measured return data to estimate model parameters by means of de-noising cross-correlation algorithm and coherence function optimization. Then, the amplitudes and phases of the received signals can be compensated using the time-variant parametric model, so that complete coherence can be achieved. Finally, background subtraction can be implemented on the amplitude and phase compensated data, resulting in exact background subtraction. The experimental results are presented to demonstrate the feasibility and usefulness of the proposed technique.