Passive Target Geo-location using Direction Finding Angles and Probability Density Matrix

Accurate geo-location of targets are extremely important in electronic warfare systems. In this paper we propose the use of probability density matrix (PDM), which is the sampled probability density function of observations, to evaluate the azimuth and elevation measurements of sensor arrays. The three dimensional joint probability density matrix of the observations will have the sufficient information to extract the location of the target. We also propose a localization algorithm to efficiently adapt the PDM domain with the latest estimation points and decrease the computational complexity. The simulation results indicate that with appropriate settings the localization algorithm can reduce the estimation error about 50%.