Target range estimation with cooperating airborne passive sensors

Range estimation with two airborne, cooperating passive sensors is shown. The estimation algorithm is a multi-hypothesis Kalman filter in Cartesian coordinates. It is shown how this concept handles situations where there is no baseline for triangulation and no line-of-sight rate. The algorithm sets no requirements on the individual sensor measurement rate and neither on measurement synchronization. The Cartesian coordinate frame gives a target model that is independent of the source of the measurements. The multiple model approach reduces the nonlinearities and decreases the numerical problems in the covariance calculations.