Optimal waveform design for target tracking and estimation in cognitive radar

Abstract

In this paper, the problem of optimal waveform design for target tracking and estimation in cognitive radar (CR) is investigated. This problem is analyzed in signal-dependent interference, as well as additive channel noise for extended target with unknown target impulse response (TIR). An improved online waveform optimization design method for target tracking and estimation is proposed. In this method, Kalman filter is used to accurately estimate the TIR. At each Kalman filtering (KF) iteration, the online waveform spectrum optimization design based on mutual information (MI) criterion is modeled in Fourier domain. Unlike most existing CR waveform optimization design with constant prior information, unknown and dynamic TIR is considered in this method. Simulation results demonstrate that CR with the proposed waveform performs better than traditional radar system with fixed waveform, and offers more flexibility.