Moving target positioning method under clock skew and clock drift conditions

Abstract

The invention discloses a moving target positioning method under clock skew and clock drift conditions, and the method comprises the steps: constructing a WLS problem which comprises four unknown quantities: the position and speed of a source node, the clock skew and the clock drift; converting a non-convex weighted least square (WLS) problem into a convex positive semidefinite programming problem by adopting a positive semidefinite relaxation method, and solving the convex positive semidefinite programming problem by utilizing an interior point method to obtain a globally optimal solution. The method has the advantages that under the condition that the clock skew and the clock drift coexist and are unknown, from the perspective of the weighted least square estimation model estimation theory and the convex optimization theory, joint estimation of the clock skew and the clock drift is achieved while position and speed estimation of a source node is achieved, the positioning precision is high, and the calculation complexity is low. The method is suitable for complex deployment environments.

Description

technical field [0001] The invention relates to a target positioning technology, in particular to a moving target positioning method under clock deviation and clock drift conditions. Background technique [0002] In recent years, with the rapid development of wireless sensor network technology, its target positioning technology has been widely used in military, industrial and civilian fields. In the existing target positioning technology, according to different signal measurement methods, it can be divided into time-of-arrival (TOA), frequency-of-arrival (FOA), time-of-arrival (time-difference-of-arrival) -arrival, TDOA), frequency-difference-of-arrival (FDOA), angle-of-arrival (AOA) and received-signal-strength (RSS), etc. Generally speaking, the target positioning method based on TOA and the target positioning method based on TDOA can achieve higher positioning accuracy. If there is relative motion between the positioning target and the sensor node, the positioning accur...

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Problems solved by technology

In the literature "Second-order cone relaxation for TOA-based source localization with unknown start transmission time (second-order cone relaxation TOA localization method under the condition of unknown initial transmission time)" (IEEE Trans.Veh.Technol.,vol.63,no .6, pp.2973-2977, 2014), Wang et al. proposed a second-order cone relaxation method for jointly estimating clock bias and source node location. Experimental results show that this method is better than the existing min-max algorithm ( min-max algorithm, MMA) has better estimation performance, however, this method is only for application scenarios where source nodes and sensor nodes are static

For positioning scenarios where there is relative motion between the positioning target and the sensor node, in the document "Passive source localization using importance sampling based on TOA and FOA measurements (Frontiers of Information)" (Frontiers of Information In Technology & Electronic Engineering, vol.18, no.8, pp.1167-1179, 2017), authors such as Liu proposed a Monte Carlo Importance Sampling positioning method based on TOA and FOA observation signals. The method can simultaneously estimate the position and velocity of the source node, and at the same time reach the Cramer-Raolower bound (CRLB) in the low-noise interval, but the method does not consider the clock synchronization problem

In the published Chinese invention patent "weighted multi-dimensional scale TOA and FOA multi-source collaborative positioning method for suppressing sensor position and velocity prior error" (patent number: ZL202010335968.5), Wang Ding et al. proposed a method to suppress sensor position The weighted multidimensional scale TOA and FOA multi-source co-location method of velocity prior error, this method uses the linear least squares (Linear Least Squares, LLS) estimation optimization model to obtain the estimated value of the position vector and velocity vector of each radiation source, although This method considers the positioning of multiple source nodes, but it also has the defect of not considering clock synchronization

Based on the existing literature, when using TOA and FOA observation signals to estimate the position and velocity of the source node, there is no feasible solution for the scenario where clock bias and clock drift exist at the same time.

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