Adaptive Detectors for Channel Matrix-based MIMO Radar

In conventional radar signal processing, a structured model is typically assumed for the target response, while the co variance matrix of the radar data distribution characterizes clutter and interference. In contrast, the channel matrix-based model treats target and clutter returns as responses to corresponding channels, yielding a more generic and versatile radar data model. Leveraging this framework, and assuming the availability of primary and secondary data sets, this paper derives Generalized Likelihood Ratio Test (GLRT) statistics for adaptive target detection in a multiple input multiple-output (MIMO) radar system under the assumption of a complex multivariate elliptically symmetric (CMES) data distribution. We consider two scenarios: one where the covariance of waveform-independent colored noise (WICN) is known and another where it is unknown. The statistical performance of the resulting GLRTs is also analyzed. Additionally, Monte Carlo (MC) simulations and the saddle point approximation (SPA) are employed to generate receiver operating characteristic (ROC) curves for a simple numerical example, with experimental results and high f idelity simulations further substantiating our findings.

Duke Scholars

Author Christ D Richmond Pierre R. Lamond Department of Electrical and Computer Engin ...