A new algorithm for Passive Bistatic Radar (PBR) localization exploiting multiple illuminators of opportunity is proposed. To capitalize a-priori information on the receiving antenna main-lobe extent, specific constraints are forced to the target localization process. At the estimator design process the elliptic positioning problem is formulated according to the constrained Least Squares (LS) framework. Hence, the resulting non-convex optimization problem is globally solved providing a closed-form estimate to the target Cartesian coordinates. At the analysis level, the performance of the new estimator is assessed in terms of Root Mean Square Error (RMSE) behavior. The results highlight that interesting MSE improvements with respect to some counterparts available in the open literature can be achieved especially at low Signal to Noise Ratio (SNR) values.
Localization in 2D PBR with Multiple Transmitters of Opportunity: A Constrained Least Squares Approach
Pallotta L.
2020-01-01
Abstract
A new algorithm for Passive Bistatic Radar (PBR) localization exploiting multiple illuminators of opportunity is proposed. To capitalize a-priori information on the receiving antenna main-lobe extent, specific constraints are forced to the target localization process. At the estimator design process the elliptic positioning problem is formulated according to the constrained Least Squares (LS) framework. Hence, the resulting non-convex optimization problem is globally solved providing a closed-form estimate to the target Cartesian coordinates. At the analysis level, the performance of the new estimator is assessed in terms of Root Mean Square Error (RMSE) behavior. The results highlight that interesting MSE improvements with respect to some counterparts available in the open literature can be achieved especially at low Signal to Noise Ratio (SNR) values.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
