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  • Open Access

    ARTICLE

    INS-GNSS Integrated Navigation Algorithm Based on TransGAN

    Linxuan Wang1,*, Xiangwei Kong1, Hongzhe Xu2, Hong Li1

    Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 91-110, 2023, DOI:10.32604/iasc.2023.035876 - 29 April 2023

    Abstract With the rapid development of autopilot technology, a variety of engineering applications require higher and higher requirements for navigation and positioning accuracy, as well as the error range should reach centimeter level. Single navigation systems such as the inertial navigation system (INS) and the global navigation satellite system (GNSS) cannot meet the navigation requirements in many cases of high mobility and complex environments. For the purpose of improving the accuracy of INS-GNSS integrated navigation system, an INSGNSS integrated navigation algorithm based on TransGAN is proposed. First of all, the GNSS data in the actual test… More >

  • Open Access

    ARTICLE

    Application of Low Cost Integrated Navigation System in Precision Agriculture

    Qi Wang1,2,3,*, Changsong Yang2,3,5, Yuxiang Wang1,2,3, Shao-en Wu4

    Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1433-1442, 2020, DOI:10.32604/iasc.2020.012759 - 24 December 2020

    Abstract To improve the positioning accuracy of farming vehicle in precision agriculture, an integrated positioning system is proposed based on Global Navigation Satellite System (GNSS)/Strapdown Inertial Navigation System (SINS)/Wireless Sensor Networks (WSN) with low cost and high reliability. The principles of commonly used localization technologies in vehicle positioning are compared and the Received Signal Strength Indication (RSSI) based measurement method is chosen as the integrated positioning system for information fusion considering the complexity of the algorithm, positioning accuracy and hardware requirements in the application scenario. The research of wireless signal propagation loss model of farmland environment More >

  • Open Access

    ARTICLE

    Improved Adaptive Particle Filter for Integrated Navigation System

    Mengchu Tian1, Yuming Bo1, Zhimin Chen2,3, Panlong Wu1, Gaopeng Zhao1

    CMES-Computer Modeling in Engineering & Sciences, Vol.108, No.5, pp. 285-301, 2015, DOI:10.3970/cmes.2015.108.285

    Abstract Particle filter based on particle swarm optimization algorithm is not precise enough and easily trapping in local optimum, it is difficult to satisfy the requirement of advanced integrated navigation system. To solve these problems, an improved adaptive particle filter based on chaos particle swarm was proposed and used in GPS/INS integrated navigation system. This algorithm introduced chaos sequence to update the weight and threshold, which could improve the quality of samples and reduce the local optimization and enhance the global searching ability. In addition, the avoid factor was set which made the particles be away More >

  • Open Access

    ARTICLE

    Hybrid Adaptive Particle Swarm Optimized Particle Filter for Integrated Navigation System

    Zhimin Chen1,2, Yuanxin Qu1, Tongshuang Zhang1, Xiaoshu Bai1, Xiaohong Tao1, Yong Liu1

    CMES-Computer Modeling in Engineering & Sciences, Vol.106, No.6, pp. 379-393, 2015, DOI:10.3970/cmes.2015.106.379

    Abstract Particle swarm optimization algorithm based particle filter is trapping in local optimum easily, it is not able to satisfy the requirement of modern integrated navigation system. In order to solve the problem, A novel particle filter algorithm based on hybrid adaptive particle swarm optimization(HPSO-PF) is presented in this paper. This improved particle filter will conduce to finding the ideal solution domain by making use of the global convergence of artificial fish swarm and enhancement of fusion precision by guiding particles to move toward the high likelihood area through particle swarm optimization. Finally different models are More >

  • Open Access

    ARTICLE

    A New Optimized Algorithm with Nonlinear Filter for Ultra-Tightly Coupled Integrated Navigation System of Land Vehicle

    Chien-Hao Tseng1, Dah-Jing Jwo2, Chih-Wen Chang1

    CMC-Computers, Materials & Continua, Vol.27, No.1, pp. 23-54, 2012, DOI:10.3970/cmc.2012.027.023

    Abstract The extended particle filter (EPF) assisted by the Takagi-Sugeno (T-S) fuzzy logic adaptive system (FLAS) is used to design the ultra-tightly coupled GPS/INS (inertial navigation system) integrated navigation, which can maneuver the vehicle environment and the GPS outages scenario. The traditional integrated navigation designs adopt a loosely or tightly coupled architecture, for which the GPS receiver may lose the lock due to the interference/jamming scenarios, high dynamic environments, and the periods of partial GPS shading. An ultra-tight GPS/INS architecture involves the integration of I (in-phase) and Q (quadrature) components from the correlator of a GPS… More >

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