Time difference of arrival based multiple source localization Taylor slack-partial iteration algorithm

Abstract

The invention discloses a time difference of arrival based multiple source localization Taylor slack-partial iteration algorithm which comprises the steps of firstly constructing an original problem model; slacking non-convex constraint of an original problem to convex constraint by means of a Taylor slack method, slacking an integer variable to a continuous variable; obtaining an initial point required for the algorithm through coarse semi-definite relaxation and secondary cone relaxation; obtaining an integer solution by means of bipartite matching; and introducing the obtained integer solution into the model, and calculating the optimal estimated coordinate value of each to-be-positioned object. According to the algorithm of the invention, the non-convex constraint is converted to convex constraint by means of Taylor slack; and furthermore discrete the integer variable is slacked to a continuous variable, thereby greatly reducing complexity of the original problem, improving solvability of the problem. Under a precondition that the initial point is properly selected and base station are laid reasonably, a whole-domain optical solution can be obtained.

Description

technical field [0001] The invention belongs to the technical field of positioning based on wireless signals, and in particular relates to a convex optimization algorithm for multi-target positioning problems, which is suitable for multi-target positioning problems based on TDOA. Background technique [0002] Wireless positioning technology was first used to locate military targets such as ships and fighter jets during World War II. With the development of science and technology, more and more wireless positioning technology has been widely used in the fields of industry, civil and national defense. Such as emergency rescue response, real-time tracking of dangerous goods, mobile phone positioning, process control. Improving the estimated speed and accuracy of wireless positioning algorithms through mathematical methods has always been a research hotspot in related fields. [0003] Thanks to the development of convex optimization algorithms, efficient convex optimization re...

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Problems solved by technology

[0005] For above-mentioned deficiencies in the prior art, the object of the present invention is to propose a kind of Taylor relaxation-subdivision iterative algorithm (time difference of arrival based multiple source localization problem TDOA-MSL) based on time difference of arrival (TDOA), this algorithm The most prominent advantage is that using Taylor relaxation to transform non-convex constraints into convex constraints, and relaxing discrete integer variables into continuous variables can greatly reduce the complexity of the original problem and improve the solvability of the problem. On the premise of a reasonable layout of base stations, the global optimal solution can be obtained

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