Combined vehicle position measurement method

Abstract

The invention provides a simple and reliable inertia/GPS (global positioning system)/milemeter combined algorithm for solving the precision positioning problem of vehicles in complex environments, such as bridges, trees, tunnel barriers, urban canyons and the like. The method comprises the following steps of: respectively independently calculating position information of a carrier through an inertia/GPS combined navigation algorithm and a milemeter dead reckoning algorithm, further fusing the position information obtained by calculation through the two different algorithms through an output correction filter with simple design, and finally giving out high-precision vehicle position information. Compared with a traditional single-filter deep combined algorithm, the method has the advantages of stronger environmental adaptability, no sensitivity to error models of GPS, inertial navigation and a milemeter, high reliability, high output precision, easiness in implementation and the like, and can well solve the precision positioning problem of the vehicles in the complex environments.

Description

technical field [0001] The application relates to a method for measuring a dynamic position of a vehicle, and relates to the fields of inertial navigation, satellite navigation and mobile measurement. The method described in this application can be widely applied to high-precision, high-dynamic, real-time position measurement of various vehicles. Background technique [0002] Vehicle position measurement is a key technical problem that must be solved in application fields such as vehicle navigation, road mapping, and electronic transportation. Currently the most commonly used means of position measurement is the GPS positioning system, such as car navigators, etc., but relying solely on the GPS system for position measurement often has the following problems: (1) GPS signals are easily blocked and interrupted: in bridges, tunnels, trees, cities, etc. In environments such as canyons, GPS cannot provide continuous and accurate location information. (2) GPS signals are suscep...

AI Technical Summary

Problems solved by technology

Currently the most commonly used means of position measurement is the GPS positioning system, such as car navigators, etc., but relying solely on the GPS system for position measurement often has the following problems: (1) GPS signals are easily blocked and interrupted: in bridges, tunnels, trees, cities, etc. In environments such as canyons, GPS cannot provide continuous and accurate location information

(2) GPS signals are vulnerable to multi-path interference and cause positioning errors. At this time, the position given by GPS will have a large error

But the inertial / GPS position measurement system also has an inevitable problem: when the GPS is invalid for a long time, the position error of the inertial navigation system will increase rapidly with time, especially if the low-cost MEMS inertial navigation system is selected, if the GPS signal is lost for 10 Seconds, the position error of the inertial navigation system will exceed 10m, which cannot meet the requirements of high-precision position measurement

[0004] In order to overcome the above problems, some units have begun to use the combined position measurement scheme of inertial navigation, GPS, and odometer, but according to literature reports, the information currently used is to integrate the information of inertial navigation, GPS, and odometer In-depth combination scheme, this kind of scheme often has higher requirements on the resolution of the odometer. In the case of low resolution of the odometer, the output position error after system combination is relatively large. In addition, this method uses a The filter algorithm for deep fusion of three sensor information is relatively complex and difficult to implement. When the resolution of the odometer changes or when the error characteristics of inertial navigation and GPS change, the parameters of the filter must be carefully adjusted. In order to ensure the accuracy of the output position, if the parameters of the filter are not adjusted accordingly, the position accuracy of the system output will be greatly reduced

In short, although the existing combined algorithms of inertial navigation, GPS, and odometer can solve the problem of high-precision and continuous position measurement, there are inevitably complex algorithms, high requirements for devices, and poor adaptability to different devices. Weaknesses such as weak points, there are certain difficulties in wide-scale promotion and use

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