Heuristic Search-Based Detection in Polarimetric Radar for Unmanned Aerial Vehicle

‍ ‍To address the detection challenges posed by the low observability and high maneuverability of unmanned aerial vehicle （UAV） targets in complex electromagnetic environments， we propose a heuristic search-based detection method in polarimetric radar for UAV. By establishing a heuristic search framework that integrates kinematic， acceleration， and polarimetric-energy-consistency constraints， this approach effectively overcomes the limitations of high computational complexity and poor adaptability to maneuvering inherent in conventional multi-frame detection methods. First， we constructed a three-dimensional state space based on the time-range-velocity data matrix derived from short-time Fourier transform-processed radar signals. Second， we designed a multi-constraint heuristic function. We established kinematic constraints on a velocity-range mapping model through kinematic equations to derive inter-frame reachable regions for search space compression. We also incorporated acceleration constraints including penalty terms to suppress non-physical maneuver trajectories. And we set polarimetric-energy-consistency constraints to realize a cross-validation mechanism combining geometric mean and minimum value criteria by leveraging the energy focusing characteristics of dual-polarization channels. Finally， we unified these three constraints into a heuristic-function-based evaluation criterion via linear weighting， with dynamic pruning and path optimization achieved through the greedy best-first search method. Simulation results demonstrate that the proposed method achieves detection rates exceeding 80% for constant-velocity targets， uniformly accelerated targets， and time-varying accelerated targets when the signal-to-noise ratio exceeds 5 dB， significantly outperforming traditional detection methods featuring constant false alarm rate. Furthermore， the required signal-to-noise ratio for attaining trajectory correctness rates greater than 80% was reduced by over 5 dB compared to conventional approaches. Validation using real measured data demonstrates continuous trajectory detection capability for both fixed-wing and rotary-wing UAV under fluctuating signal-to-noise ratio conditions. Both simulation analysis and real measured data validation confirm that the proposed multi-constraint heuristic search mechanism enables effective detection of complex maneuvering UAV through synergistic optimization of physical principles and observational data.