Nonlinear Estimation with Radar Observations

The nonlinearities of the radar measurement model equation are examined and their influence upon the accuracy of filtering and smoothing is determined. A simple algorithm by which the effects from these nonlinearities can be significantly reduced is derived. It consists of processing the radar observations in this order: azimuth, elevation, and range, using the azimuth residual to evaluate the elevation residual, and then using this combined result to evaluate the range residual. The accuracy of estimates obtained via the algorithm is compared with and shown to be superior to that of the extended Kalman filter (EKF). Furthermore, use of the algorithm does not increase the computational complexity of estimation beyond that of the EKF.