2015Advances in intelligent systems research/Advances in Intelligent Systems ResearchOpen access

SINS and Dual Odometers Based on Integrated Navigation System

Shun Zhu, Xiaonian Wang, Zhuping Wang, Zhu Jin

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Abstract

The strapdown inertial navigation system is being broadly applied for land vehicle positioning and navigation because of its complete autonomy.To restrain the positioning error accumulation along with time of S INS more effectively and achieve higher precision of navigation, a method of the dual odometers assisting S INS to obtain more accurate velocity and direction angle information is presented in this paper.Based on the establishment of the error state and observation model of S INS and dual odometers based integrated navigation system, the general and feasible Kalman filtering algorithm is listed correspondingly.The S INS /dual odometers integrated navigation method was validated by a comparison experiment among the single S INS system, S INS /OD integrated navigation system and S INS /dual OD based integrated navigation system, the results of which examines the high performance and indicates the superiority of the proposed method.

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The strapdown inertial navigation system is being broadly applied for land vehicle positioning and navigation because of its complete autonomy.To restrain the positioning error accumulation along with time of S INS more effectively and achieve higher precision of navigation, a method of the dual odometers assisting S INS to obtain more accurate velocity and direction angle information is presented in this paper.Based on the establishment of the error state and observation model of S INS and dual odometers based integrated navigation system, the general and feasible Kalman filtering algorithm is listed correspondingly.The S INS /dual odometers integrated navigation method was validated by a comparison experiment among the single S INS system, S INS /OD integrated navigation system and S INS /dual OD based integrated navigation system, the results of which examines the high performance and indicates the superiority of the proposed method.

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Available abstract

The strapdown inertial navigation system is being broadly applied for land vehicle positioning and navigation because of its complete autonomy.To restrain the positioning error accumulation along with time of S INS more effectively and achieve higher precision of navigation, a method of the dual odometers assisting S INS to obtain more accurate velocity and direction angle information is presented in this paper.Based on the establishment of the error state and observation model of S INS and dual odometers based integrated navigation system, the general and feasible Kalman filtering algorithm is listed correspondingly.The S INS /dual odometers integrated navigation method was validated by a comparison experiment among the single S INS system, S INS /OD integrated navigation system and S INS /dual OD based integrated navigation system, the results of which examines the high performance and indicates the superiority of the proposed method.

Key concepts: Odometer, Inertial navigation system, Navigation system, Dual (grammatical number), Kalman filter, Computer science, Global Positioning System, Dead reckoning

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