Radar Code Design to Optimize Detection Performance and Measurement Accuracy for Track Maintenance

This paper considers radar slow-time code design for track maintenance in the colored Gaussian interference. The output signal-to-interference-plus-noise ratio (SINR) and Cramér Rao bounds (CRBs) on time delay and Doppler shift are used as figures of merit. The transmitted code is subject to radar power budget requirements and a similarity constraint. To tackle the resulting non-convex multi-objective optimization problem, a polynomial-time algorithm that integrates scalarization and tensor-based relaxation methods is developed. Numeral results demonstrate the trade-off between the detection and the estimation performance achieved by the proposed algorithm.