文献类型：期刊文献

英文题名：Improving GNSS Navigation and Control with Electronic Compass in Unmanned System

作者：Han, Xi[1,2,3];Zhang, Xiaolin[1];Liu, Yuansheng[2,3]

第一作者：韩玺;Han, Xi

通讯作者：Han, X[1];Han, X[2];Han, X[3]

机构：[1]Beijing Univ Aeronaut & Astronaut, Sch Elect & Informat Engn, 37 Xueyuan Rd, Beijing 100083, Peoples R China;[2]Beijing Union Univ, Coll Robot, 97 Beisihuan East Rd, Beijing 100101, Peoples R China;[3]Beijing Union Univ, Beijing Engn Res Ctr Smart Mech Innovat Design Se, 4 Gongti North Rd, Beijing 100027, Peoples R China

第一机构：Beijing Univ Aeronaut & Astronaut, Sch Elect & Informat Engn, 37 Xueyuan Rd, Beijing 100083, Peoples R China

通讯机构：[1]corresponding author), Beijing Univ Aeronaut & Astronaut, Sch Elect & Informat Engn, 37 Xueyuan Rd, Beijing 100083, Peoples R China;[2]corresponding author), Beijing Union Univ, Coll Robot, 97 Beisihuan East Rd, Beijing 100101, Peoples R China;[3]corresponding author), Beijing Union Univ, Beijing Engn Res Ctr Smart Mech Innovat Design Se, 4 Gongti North Rd, Beijing 100027, Peoples R China.|[11417]北京联合大学;[1141739]北京联合大学机器人学院;

年份：2019

卷号：23

期号：3

起止页码：427-436

外文期刊名：JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS

收录：EI(收录号：20192607123210);Scopus(收录号：2-s2.0-85067924377);WOS:【ESCI(收录号:WOS:000468345300008)】；

基金：This study was financially supported by "Talents Cultivation and Cooperation Oriented to Intelligent Vehicle Industrialization, Newton Fund Project," "The Algorithms Research of Target Tracking and Identifying and System Design Based on DSP, General program of science and technology development project of Beijing Municipal Education Commission," "Research on Multi-Agent Cooperative Location Based on V2X Technology in Uncertain Environment, Natural Science Foundation of China project," and "Academic Human Resources Development in Beijing Union University" (UK-CIAPP\324& KM201211417003& 61803034& BPHR2017EZ02).

语种：英文

外文关键词：GNSS; electronic compass; BP-PID; neural network; unmanned system

摘要：This paper proposes a compensation technique for the global navigation satellite system (GNSS)/real-time kinematic (RTK) course angle data using an electronic compass for an unmanned system. Additionally, the proportion, integral, and derivative control based on a back-propagation neural network (BPPID) is introduced to improve the steering safety and riding comfort. The course angle jitter was determined. Because the GNSS/RTK receiver cannot offer stable heading data under specific conditions, including but not limited to susceptibility to obstacles, complex electromagnetic environment, and fewer satellites. The compensation algorithm is based on the determination of the GNSS course angle variance ratio and the asynchronous characteristic between the GNSS and an electronic compass. The combined data provide accurate and robust navigation information for an outdoor unmanned system. To address the limitation of the in-system parameter adjustment, a backpropagation (BP) neural network is adhibited to a conventional proportion, integral, and derivative (PID) lateral control system. The BP-PID control module updates the incremental PID parameters through self-learning, and results in the smoother operation of the vehicle. The flowchart of the learning algorithm and method of calculating the parameters are presented. A typical measurement was conducted and the obtained results were compared with typical RTK navigation results. Thus, the effectiveness of the proposed compensation method was confirmed.