AN ADAPTIVE EXTENDED KALMAN FILTER FOR ANGLES-ONLY TRACKING INTERCEPTPROBLEMS/

When angles-only measurements are used to estimate a target's ''state' ' in tracking/intercept problems, closing geometries frequently encoun tered exhibit poor observability of some parameters which can result i n divergence of the filter. In order to help mitigate the effects of p oor observability, an adaptive extended Kalman filter has been develop ed to improve the accuracy of the estimates of relative position and v elocity and the acceleration of a target using the angles-only informa tion. This adaptive filter is based upon ridge-type estimation techniq ues and includes the computation of a biasing parameter, which provide s a measure of the overall error in the solution and is used as input into the process noise matrix required in tuning the extended Kalman f ilter. The use of this adaptive filter will allow the tuning parameter s to be adjusted each time an observation is processed. This adaptive extended Kalman filter is applied to a six degree-of-freedom homing in tercept problem where angular measurements of the target's azimuth and elevation, relative to the interceptor, are the only measurements pro vided. Results are obtained for a number of different engagement geome tries and are compared to the results obtained using both an untuned e xtended Kalman filter and a manually-tuned extended Kalman filter. Com parisons are made based upon the miss distance of the engagement as we ll as overall filter performance. Results show that the adaptive filte r is similar in accuracy to that of the manually-tuned filter but is m ore responsive to errors in the estimates.