“低慢小”目标的雷达与光电复古探测跟踪方法

Radar and opto-electrical composite detection and tracking method for “low,slow and small” targets

摘要:

针对单一探测方式难以对“低慢小”目标进行全天候探测与跟踪，采用雷达与光电的主被动复合探测技术，结合两者的优势，提高定位精度，实现脉冲多普勒雷达扫描探测引导光电系统精跟踪。首先利用四元数法建立雷达坐标系与光电坐标系的空间配准模型，雷达与光电系统空间配准后，光电接收到目标位置信息视场自动转向目标；当雷达与光电探测到同一目标，通过最小二乘法将雷达与光电探测目标数据进行加权时间配准，最后将配准后的数据采用扩展卡尔曼滤波交互多模型算法(EKF-IMM)进行滤波预测，改善复合探测系统能持续跟踪能力，同时对目标在不同运动状态下具有强适应性。仿真与实验分析表明通过复合探测的方法实现对目标进行探测跟踪，利用EKF-IMM算法降低了噪声干扰，提高了目标跟踪能力及精度，其精度较传统模型提高了7%左右。

Abstract:

In view of the difficulty of detecting and tracking for the target of "low, slow and small" all-weather detection by a single detection method, the active and passive composite detection technology of radar and opto-electronic system is used, combining the advantages of both to improve the positioning accuracy, and realize the precision of the pulsed Doppler radar scanning detection, then guide opto-electronic system to track accurately. Firstly, the quaternion method is used to establish the spatial registration model of the radar coordinate system and the opto-electronic coordinate system, and the data after the spatial registration is transmitted to the photoelectric system, and the optical TV field will automatically turn to the target; when the radar and the opto-electronic detect the same target, The weighted time registration of radar and photoelectric detection target data is carried out by the least square method, and finally the registered data is filtered and predicted by the extended Kalman filter interactive multi-model algorithm (EKF-IMM), which improves the continuous tracking ability of the composite detection system, at the same time It has strong adaptability to the target in different motion states. The simulation and experimental analysis show that the target is detected and tracked by the method of composite detection, and the EKF-IMM algorithm is used to reduce the noise interference and improve the target tracking ability and accuracy,The precision of the model is about 7% higher than that of traditional model.