OPTIMIZATION OF THE TRAJECTORY OF SENSORS MOTION TAKING INTO ACCOUNT THE IMPORTANCE OF THE AREAS OF THE MONITORING AREA SEGMENTS AND THE PROBABILITY OF DETECTION OF OBJECTS

Abstract

Due to the widespread use of sensors in data collection and processing, one of the key criteria is the amount of information accumulated and energy efficiency. While monitoring the territory, the movement of research objects is common. As a result there is a change in the probability of their detection in the segment of the territory. Also, segments may be of varying importance. Taking these factors into account will significantly increase the amount of information accumulated. The article presents a method of constructing the optimal trajectory of sensors motion taking into account the importance of territory segments and the probability of detection of objects. The method is based on the representation of distribution of the probability of detection of objects and the importance of territory segments in the form of layers and their integration into a layer of the probable value of detected objects. Seven classes of the probable value of detected objects with corresponding numerical and graphical equivalents are considered. As optimal trajectory of sensors motion the trajectory which provides minimum energy expenditure is meant. Energy efficiency is achieved by constructing a trajectory of minimum length as a solution to the salesman’s problem. The set of points at which the trajectory is built is formed on the basis of the layer of the probable value of the detected objects after the procedure of replacing the nodes. A separate node replacement class, or superposition of node replacement classes, is proposed for each class of probable value of detected objects. Replacement of five, three and two nodes is described. A genetic algorithm with modification of crossing and selection rules was used to find a solution to this problem. A set of trajectories is constructed using the proposed algorithm. The analysis of the obtained results confirmed the efficiency of the developed method and allowed to increase the energy efficiency when covering a given area by 76 %.