NLS-based Registration Algorithm for Bearings-Only Location by Multiple Airborne Observers

Registration for passive sensors on multiple airborne observers is one of difficult multi-sensor registration problems. The accuracy of location will be severely affected when the measurements taken by passive sensors consist of systematic biases without registration. A registration algorithm based on nonlinear least-squares (NLS) for bearings-only location by multiple airborne observers is proposed. The algorithm regards registration for multiple airborne bearings-only observers as an NLS problem, and solves it by Gauss-Newton Method. Firstly, linearize the measurement equations and estimate the parameters using the general least-squares method. Then execute the iterative procedure until the estimated parameters converge to optimal estimations. Simulation results show that, given enough measurements, the NLS-based registration algorithm proposed here can effectively estimate the systemic biases as well as the position of the target with the location error reaching the Cramer-Rao bound (CRLB) when compared with EKF-based registration algorithm.