Enhanced Target Localization With Deployable Multiplatform Radar Nodes Based on Non-Convex Constrained Least Squares Optimization

A new algorithm for 3D localization in multiplatform radar networks, comprising one transmitter and multiple receivers, is proposed. To take advantage of the monostatic sensor radiation pattern features, ad-hoc constraints are imposed target process. Therefore, problem formulated as a non-convex constrained Least Squares (LS) optimization which globally solved quasi-closed-form leveraging Karush-Kuhn-Tucker (KKT) conditions. The performance assessed terms Root Mean Square Error (RMSE) comparison with benchmark Cramer Rao Lower Bound (CRLB) some competitors from open literature. results corroborate effectiveness strategy capable ensuring lower RMSE than counterpart methodologies especially low Signal to Noise Ratio (SNR) regime.