Fault tolerant integrated radar/inertial altimeter based on Nonlinear Robust Adaptive Kalman filter

Abstract

Abstract The fault tolerant integrated navigation system, consisting of radar and inertial altimeters, is presented. In the open loop system, the inertial altimeter is the main source of information, and radar altimeter provides discrete aiding data to support the estimations. The integration is achieved by using a Nonlinear Robust Adaptive Kalman Filter with the filter gain correction based on the evaluation of the posterior probability of the normal operation of altimeter, given for current measurement. This probability is proposed to calculate via the posterior probability density of the normalized innovation sequence at the current estimation step. In the proposed filtration algorithm, the filter gain is corrected by multiplying with the mentioned posterior probability, which plays the role of the weight coefficients to the innovation vector. As a result, faults in the estimation system are corrected by the system, without affecting the good estimation behavior. The performance of the proposed fault tolerant integrated radar/inertial altimeter is tested for the different types of measurement faults; instantaneous abnormal measurements, continuous bias at measurements, measurement noise increment and fault of zero output.