Research on clutter suppression method based on velocity distribution in vegetation clutter environment

Abstract

A radar is a kind of radio detection equipment that is often used as a sensor for target detection and location. In modern border defense work, monitoring, early warning, and others are often based on the vegetation environment. Therefore, detecting concealed personnel targets in a vegetation environment is of great significance. Generally, the motion of branches, leaves, and plants under natural conditions will produce strong vegetation clutter, resulting in many false alarms and a sharp decrease in detection probability. To find a reasonable way to suppress vegetation clutter, this paper focuses on vegetation clutter modeling and filter designing. Firstly, we review previous research on clutter suppression and find most of the clutter modeling work focused on clutter itself but ignored the velocity difference between clutter and target, which can be used for clutter suppression. Then, the velocity distributions of vegetation clutter and targets are extracted from measured data. According to the intersection of two velocity distribution fitting curves with the least mean square error, the filter’s cutoff frequency is calculated, and an optimal signal-to-noise ratio filter is designed based on the Neyman-Pearson criterion. Finally, an experiment on vegetation clutter suppression was completed. Results show that the proposed method can achieve an average of 8.2 dB and 11 dB improvement in signal-to-noise ratio compared with traditional suppression methods.