Cooperative positioning method based on sequential consistent weighted sum-product algorithm
A collaborative positioning and consistent technology, applied in the direction of electrical components, wireless communication, network topology, etc., can solve problems such as unguaranteed convergence
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Publication Date
- 2017-01-18
- Estimated Expiration
- Not applicable · inactive patent
Smart Images

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Abstract
Description
technical field
[0001] The invention relates to a cooperative positioning method based on a sequential consistent weighted sum product algorithm, which belongs to the technical field of positioning. Background technique
[0002] As a graphical means of visually representing mathematical functions and problems, factor graphs can concretize abstract mathematical problems and mathematical calculation processes into message calculation and message transmission on factor graphs. On the basis of the factor graph, a general algorithm for calculating the marginal distribution of the global function through message passing on the corresponding probability graph model is developed, that is, the sum-product algorithm. Factor graph and its sum-product algorithm have been widely used in cooperative localization in wireless sensor networks. The current Belief Propagation Algorithm (BP), Forward-Backward Algorithm, Viterbi Algorithm, and Turbo Decoding Algorithm and other algorithms devel...
Examples
Embodiment Construction
[0044] The present invention will be further described below in conjunction with the accompanying drawings. The following examples are only used to illustrate the technical solution of the present invention more clearly, but not to limit the protection scope of the present invention.
[0045] Such as figure 1 As shown, the collaborative positioning method based on the sequential consistent weighted sum product algorithm includes the following steps:
[0046] Step 1, the target node i corrects the posterior probability distribution p according to its own Nth iteration at time t-1 (N) (x i,t-1 |z 1:t-1 ) and its own state equation at time t, calculate its prior probability distribution p(x i,t |z 1:t-1 );
[0047] where i∈V T , V T Represents the set of all target nodes, x i,t-1 Indicates the position of the target node i in the two-dimensional space at time t-1, x i,t Indicates the position of the target node i in the two-dimensional space at time t, z 1:t-1 Indicate...