Patent ID: 11906616
Assignee: XIDIAN UNIVERSITY
Field: Measurement (Instruments)
Classification: CPC G  Y | IPC G

Claim 3:
4. The method according to claim 1, wherein the target tracking is performed on the continuous multi-frame RD maps obtained by the Kalman filtering method in (6), which is implemented as follows:
(6a) Obtaining an observed value Z(k) of the target at current time through target detection, clustering and centroid condensation;
(6b) Calculating a state variable X(k+1|k) and covariance matrix P(k+1|k) at the time k+1 predicted by using a tracking result at the time k according to the following formula:

X(k+1|k)=FX(k)+BU(k)+W(k),

P(k+1|k)=FP(k)FT+Q, 

Wherein F is the transformation matrix, FT is the transposition of transformation matrix, B is the control matrix, X(k) is the state variable obtained by tracking at time k, P(k) is the covariance matrix obtained by tracking at time k, U(k) is the control gain of current state, W(k) represents the noise at time k, and Q represents a covariance of system process noise;
(6c) According to the covariance matrix obtained in (6b), calculating the Kalman gain K:

K=P(k+1|k)HT(HP(k+1|k)HT+R)−1,

Wherein H is the observation matrix, HT is the transposition of the observation matrix, R represents the covariance of the object measurement noise, and (⋅)−1 represents the inversion of the elements in parentheses;
(6d) According to the state variable and covariance matrix obtained in (6b) and the Kalman gain obtained in (6c), calculating the state variable X(k+1) and covariance matrix P(k+1) obtained by tracking at time k+1:

X(k+1)=X(k+1|k)+K(Z(k)−HX(k+1|k)),

P(k+1)=(1−KH)P(k+1|k).