Optimal selection method of positioning node facing TDOA

Abstract

The invention provides an optimal selection method of positioning nodes facing TDOA, and aims to solve the technical problems that an existing method uses mass sensor nodes to participate positioning,so the existing method is large in energy consumption, high in system complexity, and low in positioning precision; the optimal selection method comprises the following steps: obtaining a covariancematrix Q of gauss white noise n; carrying out TDOA estimation so as to obtain a arrival distance difference vector r; obtaining the closed-form solution of a target source position coordinate u; calculating a covariance matrix cov (u) of the positioning errors according to the closed-form solution of the target source position coordinate u; building a positive semidefinite planning function selected by nodes; obtaining the optimal positioning node. The method can reduce the energy consumption and system complexity caused by using mass sensor nodes to participate positioning, thus effectively improving the positioning precision; the method can be applied to select sensor node combinations facing TDOA positioning.

Description

technical field [0001] The invention belongs to the technical field of signal processing, and relates to a wireless sensor network passive positioning, in particular to a TDOA-oriented positioning node optimization method, which can be used to screen out TDOA-oriented positioning node combinations to improve positioning accuracy performance. Background technique [0002] At present, positioning technology is widely used in environmental monitoring, emergency rescue work, public safety and wireless communication systems. Commonly used passive positioning techniques are mainly based on Time of Arrival (TOA), Time Difference of Arrival (TDOA), Received Signal Strength (RSS) and Angle of Arrival (AOA). The positioning technology based on TDOA is mainly used for stationary target source positioning. In wireless sensor networks based on TDOA positioning, sensor nodes are usually placed in harsh environments, so energy consumption and node network layout must be considered. First...

AI Technical Summary

Problems solved by technology

Although this technology can select as few nodes as possible that can improve performance, in the TDOA-based measurement model, because the number of TDOA measurements is smaller than the number of sensor nodes, TDOA measurement is different from the general nonlinear measurement model, so The above method cannot be used for node selection in TDOA scenarios

In the TDOA positioning scenario, typical positioning node selection methods include the global search method and the K-nearest method. The global search method is to select all sensor nodes to participate in positioning. Although this method has high positioning accuracy, it consumes a lot of energy and the system operation is complicated. The K-nearest method is to select the k nearest sensor nodes including the reference node for positioning. In practice, the node selection is performed through the receiving signal-to-noise ratio of different sensor nodes. Although this method has low computational complexity, its positioning performance is poor.

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