Technique of anti-multi-range-false-target jamming for radar network based on double discrimination

Abstract

Aiming at active multi-range-false-target deception jamming discrimination of radar network, a technique based on double discrimination of active multi-range-false-target deception jamming of radar network is proposed. Firstly, the benchmark radar is selected, target measurements from the benchmark radar are classified into groups, and the angle measurements in the same group are compressed for improving the measurement accuracy. Then, bearings only measurements association test is used for determining whether the measurements in the radar network are in the direction of the benchmark radar. Measurements passing the bearings only measurements association test will be taken the nearest neighbor association test with measurements in the classified groups of the benchmark radar. At last, the true-targets will be discriminated by double discrimination. The simulation results show that the algorithm can not only improve the correct discrimination rate comparing with the existing method but also track targets stably under the active multi-range-false-target deception jamming.