Bearings-only passive positioning method based on metaheuristic algorithm

Abstract

The invention relates to a bearings-only passive positioning method based on a metaheuristic algorithm, and aims at the situations that the sensor distribution is not fixed, the performance differencebetween sensors is larger. The positioning effect of the method has significant advantages compared with a traditional least square positioning method, and a target function needs to revised only when an observing environment changes. A paradigm of using the metaheuristic algorithm to perform target counting information fusion is provided to use the capability of the metaheuristic algorithm in solving non-convex problems, and the paradigm can solve a plurality of problems of target counting information fusion under an observing environment which can be modeled.

Description

technical field [0001] The invention belongs to the field of sensor information fusion, and in particular relates to an orientation-only passive positioning method based on a meta-heuristic algorithm. Background technique [0002] The problem of pure orientation passive positioning occurs in Wireless Sensor Networks (WSN, Wireless Sensor Network). Generally speaking, passive sensors only have the ability to obtain target orientation information. Therefore, to obtain target location information requires multiple distributed sensors. Orientation measurement for information fusion, the current positioning method in this environment is generally based on the principle of least squares ( figure 1 ). The principle of the least squares-based positioning method is: the observation result of each orientation sensor in space will form a ray at this orientation, so a ray cluster composed of multiple rays will be generated in the observation network composed of multiple sensors. The l...

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Problems solved by technology

The existing technology ignores two problems. First, when the performance gap of multiple sensors is relatively obvious, the method has no way to distinguish them. Sensors with poor performance carry less information about the target but can be indistinguishable and have excellent performance. Second, the distance from a certain point to the observation ray cannot fully represent the possibility of the point becoming a target. The distance between a point close to a certain sensor and the observation ray must be very short, but this does not guarantee It has a high probability of becoming a target

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