A Fast Power Allocation Algorithm in a Collocated MIMO Radar under Low Interception Backgrounds

Abstract

This study proposes a fast power allocation algorithm under a low interception background for a collocated MIMO radar that simultaneously tracks multiple maneuvering targets. First, the target maneuver process is modeled as an Adaptive Current Statistical (ACS) model, and a particle filter is used to estimate the state of each target. Second, the Predicted Conditional Cramer-Rao Lower Bound (PC-CRLB) is derived, and the target comprehensive threat assessment model is constructed based on the target motion and electromagnetic characteristics. Subsequently, an optimization model with respect to transmitting power is established by developing the weighted sum of the target tracking error evaluation index and the unintercepted probability of radar as the optimization objective. Thereafter, to solve the model using the monotonically decreasing property of the objective function, a solving algorithm based on sequence relaxation is proposed. Finally, a simulation is conducted to verify the effectiveness and timeliness of the proposed algorithm. The results indicate that the proposed algorithm can effectively improve the target tracking accuracy and low interception performance of the radar system. Further, its run speed is increased by nearly 50% compared with that of the interior point method.

Keywords

• collocated mimo radar
• power allocation
• maneuvering tracking
• low interception performance
• predicted conditional cramer-rao lower bound (pc-crlb)