Nonlinear Adaptive Joint Detection/Estimation for Multi-Radar Data Fusion

This paper addresses the problem of multisensor detection and high resolution signal parameter estimation using joint maximum a posteriori detection and high order nonlinear filtering techniques. The model-based fusion approach offers the potential for increased target resolution in range/azimuth space. The technique employs joint detection/estimation (JDE) filters for target detection and target parameter localization. The JDE approach segments the aggregate nonlinear model over the entire target resolution space into resolution subcells. This partitioning leads to extremely accurtate detection and parameter estimation. The proposed JDE approach has a built-in capability for automatic data alignment from multiple sensors, and can be used for centralized, noncentralized, and distributed data fusion.