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%.
 T. Michael, G. Hamschin and B. M. Hamschin, "Geo-Location Using Direction Finding Angles," Johns Hopkins APL Technical Digest, vol. 31, no. 3, pp. 254-262, 2013.
 R. Stansfield, "Statistical theory of d.f. fixing," Journal of the Institution of Electrical Engineers - Part IIIA: Radiocommunication, , vol. 94, no. 15, pp. 762-770, 1947.
 W. Foy, "Position-Location Solutions by Taylor-Series Estimation," IEEE Transactions on Aerospace and Electronic Systems, vol. 12, no. 2, pp. 187-194, 1976.
 D. Torrieri, "Statistical Theory of Passive Location Systems," IEEE Transactions on Aerospace and Electronic Systems, Vols. AES-20, no. 2, pp. 183-198, 1984.
 D. Wangsness, "A New Method of Position Estimation Using Bearing Measurements," IEEE Transactions on Aerospace and Electronic Systems, , Vols. AES-9, no. 6, pp. 959-960, 1973.
 L. Paradowski, "Unconventional algorithm for emitter position location in three-dimensional space using data from two-dimensional direction finding," in Proceedings of the IEEE 1994 National Aerospace and Electronics Conference, NAECON , Dayton, OH, 1994.
 A. Pages-Zamora, J. Vidal and D. Brooks, "Closed-form solution for positioning based on angle of arrival measurements," IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, vol. 4, pp. 1522-1526, 2002.
 Z. Zhao, X. Wang, S. Xiao and D. Dai, "Grid-based probability density matrix for multi-sensor data fusion," in Asia Pacific Conference on Postgraduate Research in Microelectronics & Electronics, Shanghai, 2009.
 D. Elsaesser, "The Discrete Probability Density Method for Emitter Geolocation," in Canadian Conference on Electrical and Computer Engineering, CCECE '06, Ottawa, Ont., 2006.
 D. Elsaesser, "Sensor data fusion using a probability density grid," in 10th International Conference on Information Fusion, Quebec, Que, 2007.