Kalman filtering method based on finite step memory
A Kalman filtering and memory technology, applied in the field of tracking and filtering of slow moving targets, can solve the problems of missing targets, low stability, and non-convergence of tracking results, etc., to reduce tracking error, accuracy and stability Improved effect
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[0038] refer to figure 1 , the implementation steps of the present invention include as follows:
[0039] Step 1: Obtain the reference state of the target track.
[0040] Obtain the first N steps of the filter state of the target track by the traditional Kalman filter method and predicted state And the state covariance P(k-1|k-1), where k=1,2,...,N represents the moment;
[0041] Go back N steps according to the current state of the track, and the obtained filtering state is called the reference state of the target track
[0042] Step 2. According to the reference state of the target track Determine if the target is maneuvering.
[0043] refer to figure 2 , the specific implementation of this step is as follows:
[0044] 2a) According to the reference state Predict the state up to the current moment The displacement a and the predicted state at the current moment To measure the displacement c of state Z(k), calculate the angle θ between these two displacemen...
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