Abstract:

The modified scatterer density dependent (MSDD) has a certain loss of the signal-to-clutter ratio (SCR) when falsely estimating the number of scatterers in non-Gaussian clutter modelling by spherically invariant random vector (SIRV). For this problem, a modified scatterers density dependent detector based on modified entropy (ME-MSDD) is addressed. For the ME-MSDD, it estimates the number of strong scatterers by  using modified entropy firstly, and then the test statistics are formed by integrating strong scatterers. Finally, the detection performance is evaluated for different target models and the one dimension range profile of real targets. The results show that the ME-MSDD can adaptively estimate the number of target scatterers according to the observations, which can improve the performance and robustness of detectors effectively.