Development and Evaluation of Gradient-Based Numerical Algorithms for Object Localization in Multistatic Passive Radar System
Abstract
Passive radar does not transmit its own signals but relies on external sources of illumination. Estimating a target position requires distance measurements from at least three spatially separated sensors. This paper presents an adaptation of a maximum likelihood estimator (MLE) for target localization using multiple (three or more) bistatic range or DToA (Difference Time of Arrival) measurements. The Gauss–Newton, Levenberg, and Levenberg–Marquardt methods are compared with respect to numerical stability and localization accuracy under different noise levels and initialization conditions.
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