Marino, Angela (2022) Advanced Target Localization Strategies for Multiplatform Radar Systems via Constrained Optimization. [Tesi di dottorato]

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Abstract

Nowadays, the ability to locate targets is crucial for a huge number of applications which demand an ever increasing accuracy. For this reason, the design of advanced sensing systems has attracted a lot of attention in both academic and industrial contexts. The main aim of this thesis is the development of innovative localization algorithms for some sensing systems of practical relevance. Specifically, three novel techniques have been devised. The first strategy, referred to as Angular and Active Constrained Least Square (AACLS), is an algorithm for 2D Passive Bistatic Radar (PBR) localization via joint exploitation of multiple illuminators of opportunity and measurements gathered by a co-located active radar, thus representing a basic version of a Multiplatform Radar Network (MPRN). This technique exploits angular and range constraints resulting from prior knowledge of the PBR beam extent and uncertainty of active radar data. The second algorithm, denoted as Angular and Range Constrained Estimator (ARCE), is a 3D localization technique for MPRNs, comprising one transmitter and multiple receivers. In particular, ARCE leverages ad-hoc constraints in order to capitalize on the information embedded into the monostatic sensor radiation pattern features. The third technique is obtained combining ARCE and the Sum Product Algorithm (SPA)-based Multitarget Tracking (MTT) technique. Specifically, the latter is enhanced through a bespoke particles generation process exploiting the ARCE position estimate.

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