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Adaptive CPSO (Chaos Particle Swarm Optimization) integrated navigation satellite selection method

A chaotic particle swarm and integrated navigation technology, which is applied to satellite radio beacon positioning systems, measuring devices, instruments, etc., can solve problems such as complex methods, and achieve the effects of easy implementation, few parameters, and satisfactory positioning accuracy

Active Publication Date: 2018-09-28
SHENYANG AEROSPACE UNIVERSITY
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Problems solved by technology

However, the method is complex, and there are many parameters that need to be adjusted, and the practicability of the method still needs to be further explored.

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  • Adaptive CPSO (Chaos Particle Swarm Optimization) integrated navigation satellite selection method
  • Adaptive CPSO (Chaos Particle Swarm Optimization) integrated navigation satellite selection method
  • Adaptive CPSO (Chaos Particle Swarm Optimization) integrated navigation satellite selection method

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Embodiment Construction

[0039] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0040] First introduce the following concepts and definitions:

[0041] 1. Particle swarm optimization (PSO) method: It is a random optimization method based on swarm intelligence. It imitates the foraging behavior of birds, compares the search space of the problem to the flight space of birds, and abstracts each bird as a particle to represent a candidate solution to the problem. The optimal solution needed for optimization is equivalent to To find food. As a group optimization algorithm proposed by simulating the phenomenon of biological predation in nature, the PSO algorithm can solve the opti...

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Abstract

The invention discloses an adaptive CPSO (Chaos Particle Swarm Optimization) integrated navigation satellite selection method, and the method comprises the following steps: 1, extracting visible satellites observed by a receiver at a current moment according to a navigation message and an observation file, numbering the visible satellites, grouping the satellites according to the number of selected satellites, and randomly selecting N combinations from all groups to form an initial population; 2, determining a fitness function for particle evaluation; 3, continuously updating the speed and position of particles through a speed-displacement model in a PSO (Particle Swarm optimization) algorithm till a visible satellite combination meeting a condition is searched. The method is advantageousin that 1, the integrated navigation satellite selection method based on the CPSO quickly achieves the BDS / GPS integrated navigation satellite selection, and the result meets the requirements of the receiver for the positioning precision; 2, the PSO algorithm is a potential neural network algorithm, needs fewer adjustment parameters, and is easy to implement. The PSO is applied in the satellite selection process of the receiver, thereby providing a new idea for the subsequent multi-constellation satellite selection research and application.

Description

technical field [0001] The invention relates to the research on a satellite selection method for a multi-constellation satellite navigation system. Under the multi-constellation satellite navigation system, if all visible satellites are used for positioning, it will be difficult to guarantee the real-time performance of navigation. For this reason, it is necessary to select a better group of visible satellites for positioning, so that the accuracy and real-time performance of navigation and positioning are better. At this time, it is necessary to study a fast and effective satellite selection method. In view of this, this paper The invention provides a combined navigation star selection method based on adaptive chaotic particle swarm optimization. Background technique [0002] Star selection is to roughly judge the distribution of visible stars at the location of the receiver before positioning, and select the combination of visible stars with the smallest Geometric Decay of...

Claims

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Application Information

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IPC IPC(8): G01S19/28
CPCG01S19/28
Inventor 王尔申贾超颖佟刚曲萍萍何赫王延文蓝晓宇庞涛
Owner SHENYANG AEROSPACE UNIVERSITY
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