Research on Sensor Management Algorithm of Midcourse Object Tracking

Abstract

In allusion to sensor management problem of continual midcourse object tracking in the space tracking and surveillance system, a novel optimized objective function was proposed according to analysis of its restriction. Furthermore, on the basis of analyzing the disadvantages of binary particle swarm optimization based sensor management, a novel method based on real-number particle swarm optimization was proposed through dimensionality reduction and position vector improvement. Ultimately, simulation about classical midcourse object tracking scenario was executed, and the performance of several methods were compared in detail. The simulation results indicated that the novel optimized objective function could schedule sensors effectively; moreover, the proposed sensor management was a more efficient method.