US 11,838,636 B2
Method for compensating for visual-measurement time lag of electro-optical tracking system
Jun Yang, Nanjing (CN); Xiangyang Liu, Nanjing (CN); Jianliang Mao, Nanjing (CN); and Shihua Li, Nanjing (CN)
Assigned to SOUTHEAST UNIVERSITY, Nanjing (CN)
Appl. No. 17/253,558
Filed by SOUTHEAST UNIVERSITY, Nanjing (CN)
PCT Filed Jul. 8, 2019, PCT No. PCT/CN2019/095061
§ 371(c)(1), (2) Date Dec. 17, 2020,
PCT Pub. No. WO2020/220469, PCT Pub. Date Nov. 5, 2020.
Claims priority of application No. 201910361221.4 (CN), filed on Apr. 30, 2019.
Prior Publication US 2021/0191344 A1, Jun. 24, 2021
Int. Cl. H04N 23/695 (2023.01); G05B 11/32 (2006.01); G05B 11/42 (2006.01); G05B 13/02 (2006.01)
CPC H04N 23/695 (2023.01) [G05B 11/32 (2013.01); G05B 11/42 (2013.01); G05B 13/027 (2013.01)] 7 Claims
OG exemplary drawing
 
1. A method for compensating for visual-measurement time lag of an electro-optical tracking system, comprising the following steps:
step 1: installing a camera on a pitch inner frame of a two-axis inertially stabilized platform, connecting the camera to a host computer to form an electro-optical tracking system, shooting, by the camera, a tracked target in real time, extracting, by the host computer, a miss distance of the tracked target according to an image shot by the camera, and generating, by the two-axis inertially stabilized platform, a control input of the system according to the miss distance;
step 2: selecting the miss distance of the tracked target as a state of the system, and establishing a discrete-time state-space model considering visual-measurement time lag and kinematic uncertainty of the system, for example:

OG Complex Work Unit Math
wherein X(k) represents the state of the system, U(k) represents the control input of the system, Δ(k) represents the kinematic uncertainty of the system, Y(k) represents a measurement output of the system, d represents the visual-measurement time lag, B represents a control input matrix, and k represents a kth moment;
step 3: defining H(k)=Δ(k+1)−Δ(k) as a difference of the kinematic uncertainty of the system, and constructing, according to the discrete-time state-space model established in step 2, an improved generalized proportional integral observer:

OG Complex Work Unit Math
wherein Z1(k), Z2(k), and Z3(k) represent states of the observer and are respectively estimated values of X(k−d), Δ(k−d), and H(k−d), and L1, L2, and L3 represent gains of the observer;
step 4: calculating a predicted value X(k) of a state of the system and a predicted value Δ(k) of the kinematic uncertainty at a current moment according to the estimated values Z1(k) Z2(k), and Z3(k) in step 3 and the discrete-time state-space model in step 2; and
step 5: designing a compound controller U(k)=B−1(−Δ(k)−KX(k)) according to the predicted values X(k) and Δ(k) obtained in step 4 and based on a feedback linearization algorithm, wherein K represents a parameter of the controller.