Research on Complex Clutter Map Algorithm Based on Clutter Background

The clutter map CFAR processing can iteratively process the echo sampling values obtained from previous scans in time, estimate the current clutter background intensity, and achieve constant false alarm detection. This paper aims to solve the problem of detecting weak moving targets in strong ground clutter by using a complex domain clutter map detection algorithm. Compared with traditional single and biparametric models that only use amplitude information, this algorithm constructs a twodimensional feature space based on the real and imaginary parts of complex echoes and calculates dynamic thresholds based on complex variance. The covariance matrix trace value (total variance) of complex components of strong ground clutter echoes in urban backgrounds is often lower than its amplitude value. Based on actual measurement data, detection analysis shows that the detection performance of complex domain clutter map in strong terrain clutter environments is superior to traditional dual parameter and single parameter clutter map. It is feasible to perform zero Doppler channel weak target detection in this context.