Minimum mean square error estimator for mobile location using the pseudo-range TOA measurements

Abstract

Source Localization in the non-synchronous mobile system is a very important issue since it only requires synchronized clocks between the based stations (BSs) and can reduce system complexity. There are time-difference-of-arrival (TDOA) and pseudo-range time-of-arrival (TOA) based localization techniques for a non-synchronous mobile system. Although many methods and performance analysis have been proposed for TDOA technique, relatively few studies have been reported on pseudo-range TOA method. This paper proposes a novel localization algorithm based on minimum mean square error estimator (MMSEE) for pseudo-range TOA. The simulations show that the proposed method can reach its CRLB and has the better performance than the TDOA method based on maximum likelihood estimator (MLE).

Robust Kalman Filtering Based on Chi-square Increment and Its Application

“…where H 0 denotes that there is no gross error in the system and H 1 denotes that there is a gross error in the system; n is the degree of freedom of Chi-square distribution; and λ is a centralized parameter matrix. For observations with gross errors, robust estimation is usually achieved by enlarging the observation covariance noise matrix [37][38][39]. According to the above hypothesis, the robust factors are constructed with ∆χ 2 k :…”