Track-Before-Detect for Airborne Maritime Radar: Application to Real Data
Branko Ristić, Du Yong Kim, Luke Rosenberg · 2024
Consider the problem of maritime surveillance using a high-resolution airborne radar for the detection and tracking of small surface targets. This is a challenging problem as the sea clutter is spiky with a non-Gaussian amplitude distribution and contains both temporally and spatially varying characteristics. As a possible solution, we have recently proposed a Bayesian track-before-detect algorithm, which assumes a compound K-distributed clutter model with Swerling 1 target fluctuations. This paper considers a suitable modification of this algorithm to work in the range-Doppler domain and evaluates its performance on real datasets collected by the Defence Science and Technology Group’s (DSTG) Ingara X-band radar.