Sensor data fusion using a probability density grid

Abstract

A novel technique has been developed at DRDC Ottawa for fusing electronic warfare (EW) sensor data by numerically combining the probability density function representing the measured value and error estimate provided by each sensor. Multiple measurements are sampled at common discrete intervals to form a probability density grid and combined to produce the fused estimate of the measured parameter. This technique, called the discrete probability density (DPD) method, is used to combine sensor measurements taken from different locations for the EW function of emitter geolocation. Results are presented using simulated line of bearing measurements and are shown to approach the theoretical location accuracy limit predicted by the Cramer-Rao lower bound. The DPD method is proposed for fusing other geolocation sensor data including time of arrival, time difference of arrival, and a priori information.