Index for task scheduling in phased array radar

Abstract

In the task scheduling problem of phased array radar, the objective function is usually based on the time shifting rate (TSR). However, the TSR cannot achieve expected scheduling performance in non-linear filtering systems. To further improve the scheduling performance, a novel index named shifting improve rate (SIR) is proposed by analysing the influence of time shifting and its formula in Kalman filtering and expand Kalman filtering is derived. Based on SIR, a new objective function for scheduling of phased array radar tasks was designed and used the genetic algorithm to solve it. Simulated experiments are done to validate the proposed index and the new objective function. The results demonstrate that the SIR achieves better scheduling performance and tracking accuracy than TSR in non-linear filtering systems while keeping similar performance in linear filtering systems.

Keywords

• scheduling
• genetic algorithms
• kalman filters
• filtering theory
• phased array radar
• scheduling performance
• tsr
• nonlinear filtering systems
• linear filtering systems
• task scheduling problem
• objective function
• improve rate
• sir
• kalman filtering
• phased array radar tasks