Multi-Sensor Passive Localization Based on Sensor Selection

Abstract

In passive localization applications, the positioning accuracy for an emitter is highly dependent on the geometry between sensors and the target, the site error and measurement noise of sensors. We propose a sensor selection mechanism which aims to choose a subset of sensors to implement the multi-sensor passive localization. An optimization model is established by minimizing the GDOP (geometric dilution of precision), with or without the constraint on the cardinality of the selected sensor subset. The CEO (cross entropy optimization) is employed to solve the resulting complex combinatorial optimization model. Simulation experiments are conducted and simulation results demonstrate the efficiency of the proposed sensor selection scheme for multi-sensor passive localization.