Efficient RSSD-Based Source Positioning with System Parameter Uncertainties

Passive source location determination is a very active research area. In this paper, we present a received signal strength difference (RSSD) source localization method based on a total least square (TLS) estimator. Due to errors in the data vector and system matrix, the least squares (LS) and weighted least squares (WLS) methods are not applicable as they produce large bias in the location estimation. Therefore, an extension of the LS methods, called total least squares (TLS) is used to solve this problem. Due to the relationship between the data vector and system matrix, a modified TLS method is presented to achieve a closed form estimate. The advantage of this approach is that it does not require transmit power estimation as with other methods, and the complexity is low. The received signal strength difference is used to eliminate uncertainties due to the signal propagation parameters. Performance results are presented which show that the performance of the proposed method comes close to achieving the Cram´er-Rao lower bound.