Ashvini Kulkarni^1,2, P. Augusta Sophy Beulet^1,*

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 127-146, 2023, DOI:10.32604/iasc.2023.035144 - 29 April 2023

Abstract It is widely acknowledged that navigation is a significant source of between sites. The Global Positioning System (GPS) has numerous navigational advancements, and hence it is used widely. GPS navigation can be compromised at any level between position, location, and estimation, to the detriment of the user. Consequently, a navigation system requires the precise location and underpinning tracking of an object without signal loss. The objective of a hybrid environment prediction system is to foresee the location of the user and their territory by employing a variety of sensors for position estimation and monitoring navigation.… More >

Weiguang Zheng^1,2,3, Junzhu Zhang^1,2, Shanchao Wang^2,*, Gaoshan Feng², Xiaohong Xu², Qiuxiang Ma²

CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.1, pp. 489-508, 2023, DOI:10.32604/cmes.2023.025169 - 23 April 2023

Abstract The extended Kalman filter (EKF) algorithm and acceleration sensor measurements were used to identify vehicle mass and road gradient in the work. Four different states of fixed mass, variable mass, fixed slope and variable slope were set to simulate real-time working conditions, respectively. A comprehensive electric commercial vehicle shifting strategy was formulated according to the identification results. The co-simulation results showed that, compared with the recursive least square (RLS) algorithm, the proposed algorithm could identify the real-time vehicle mass and road gradient quickly and accurately. The comprehensive shifting strategy formulated had the following advantages, e.g., More > Graphic Abstract

Dah-Jing Jwo^1,*, Jen-Hsien Lai²

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2883-2898, 2021, DOI:10.32604/cmc.2021.015102 - 01 March 2021

Abstract This paper investigates the minimum error entropy based extended Kalman filter (MEEKF) for multipath parameter estimation of the Global Positioning System (GPS). The extended Kalman filter (EKF) is designed to give a preliminary estimation of the state. The scheme is designed by introducing an additional term, which is tuned according to the higher order moment of the estimation error. The minimum error entropy criterion is introduced for updating the entropy of the innovation at each time step. According to the stochastic information gradient method, an optimal filer gain matrix is obtained. The mean square error… More >

Taoyun Zhou^1,2, Baowang Lian¹, Siqing Yang^2,*, Yi Zhang¹, Yangyang Liu^1,3

CMC-Computers, Materials & Continua, Vol.56, No.2, pp. 225-245, 2018, DOI:10.3970/cmc.2018.02671

Abstract For situations such as indoor and underground parking lots in which satellite signals are obstructed, GNSS cooperative positioning can be used to achieve high-precision positioning with the assistance of cooperative nodes. Here we study the cooperative positioning of two static nodes, node 1 is placed on the roof of the building and the satellite observation is ideal, node 2 is placed on the indoor windowsill where the occlusion situation is more serious, we mainly study how to locate node 2 with the assistance of node 1. Firstly, the two cooperative nodes are located with pseudo-range… More >

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 >