CAJ | 학술논문

针对目前运动目标航路规划存在的滞后性和计算量过大等问题，提出一种适合于动态环境下动态目标的航路规划方法。首先，采用卡尔曼滤波算法对目标下一步的位置进行预测，然后，调用D倡算法以无人机当前位置为起点，目标预测位置为终点进行航路规划。同时，为了减少预测误差和保证高效的航路规划效率，该方法引用了动态的目标观测周期。由于卡尔曼滤波算法是按照递推公式来预测无人机下一步状态的，不需要很多的历史数据，所以该预测算法不仅减少了计算量，而且由于采用超前规划，使算法具有了很强的实时性。从仿真结果来看，该算法有效地缩短了航程，减少了到达目标位置的时间。
침대목전운동목표항로규화존재적체후성화계산량과대등문제，제출일충괄합우동태배경하동태목표적항로규화방법。수선，채용잡이만려파산법대목표하일보적위치진행예측，연후，조용D창산법이무인궤당전위치위기점，목표예측위치위종점진행항로규화。동시，위료감소예측오차화보증고효적항로규화효솔，해방법인용료동태적목표관측주기。유우잡이만려파산법시안조체추공식래예측무인궤하일보상태적，불수요흔다적역사수거，소이해예측산법불부감소료계산량，이차유우채용초전규화，사산법구유료흔강적실시성。종방진결과래간，해산법유효지축단료항정，감소료도체목표위치적시간。
Aiming at the problems such as hysteresis and large calculation amount during path planning of moving targets,we put forward a path planning method suitable for moving target in dynamic environments . First of all,the Kalman filter algorithm was used to estimate the next position of the target .Then,the D*algorithm was used for the path planning of the UAV by taking its current position as a starting point ,and the target's predicted position as a destination .In order to reduce the prediction error and ensure efficient route planning,the dynamic observation periods were used .Since the Kalman filtering algorithm predicts the next state of UAV according to a recursive formula,it doesn't need a lot of historical data ( one at most ) .The prediction algorithm can not only reduce the calculation cost,but also has strong real-time performance .The simulation results show that the algorithm can effectively shorten the distance and reduce the time needed for getting to the target position .