To address the problem of poor position estimation robustness of the recursive terrain matching methods in the terrain aided navigation system under flat terrain conditions,a terrain matching method based on ensemble Kalman filter and regularized particle filter(RPF)is proposed.Firstly,the horizontal position component of the vehicle and the elevation measurement value of multi-beam sonar are used as the state and measurement variables of the terrain matching system,respectively.Then,the projection-based scheme is adopted to compensate for depth errors caused by attitude changes of the vehicle.Finally,the ensemble Kalman filter is used to update the conditional proposal distribution in RPF for recursive terrain matching.The terrain matching tracking performance of the improved RPF is evaluated by using ship-borne lake test data under different initial matching position error conditions.The results show that the proposed terrain matching filter can always maintain bounded positioning errors,and has high position tracking accuracy and confidence interval estimation performance.The average terrain matching error is less than 2 grids in a prior digital terrain map with a resolution of 10 m.
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