An asynchronous sensor bias estimation algorithm utilizing targets’ positions only

Abstract

Bias estimation is a critical problem in multi-sensor tracking systems, and most existing research has focused on the bias estimation of synchronous sensors; however, in practical applications, sensor measurements are usually asynchronous. The primary contribution of this paper is that a novel algorithm using B-spline interpolation time registration to achieve asynchronous sensor bias estimation is proposed. First, measurements are transformed into synchronous data using the B-spline interpolation time registration method. The time registration results are expressed as weighted results of the measurements. Second, a pseudo measurement equation is created based on the synchronous data. Compared with the pseudo measurements of other algorithms that use weighting coefficients, which are calculated by the target’s state, including the target’s velocity and time of arrival (TOA), a pseudo measurement that only depends on the target’s position can be derived. Thus, the problem of asynchronous sensor bias estimation, particularly with manoeuvring targets, can be solved effectively by the proposed algorithm. Finally, the effectiveness of the proposed algorithm is verified by simulations with the target performing s-shaped manoeuvres. Monte Carlo simulation results indicate that the Cramer-Rao lower bound (CRLB) is achievable; thus, the proposed algorithm is statistically efficient.