Shuyu Li¹, Guozheng Zhang^{1, *}

CMC-Computers, Materials & Continua, Vol.63, No.1, pp. 223-241, 2020, DOI:10.32604/cmc.2020.07499

Abstract With the popularity of sensor-rich mobile devices, mobile crowdsensing (MCS) has emerged as an effective method for data collection and processing. However, MCS platform usually need workers’ precise locations for optimal task execution and collect sensing data from workers, which raises severe concerns of privacy leakage. Trying to preserve workers’ location and sensing data from the untrusted MCS platform, a differentially private data aggregation method based on worker partition and location obfuscation (DP-DAWL method) is proposed in the paper. DP-DAWL method firstly use an improved K-means algorithm to divide workers into groups and assign different privacy budget to the group… More >

Xianghao Hou^{1, *}, Gang Qiao¹

CMES-Computer Modeling in Engineering & Sciences, Vol.122, No.1, pp. 175-205, 2020, DOI:10.32604/cmes.2020.08452

Abstract To study the parameter estimating effects of a free-floating tumbling space target, the extended Kalman filter (EKF) scheme is utilized with different high-nonlinear translational and rotational coupled kinematic & dynamic models on the LIDAR measurements. Applying the aforementioned models and measurements results in the situation where one single state can be estimated differently with varying accuracies since the EKFs based on different models have different observabilities. In the proposed EKFs, the traditional quaternions based kinematics and dynamics and the dual vector quaternions (DVQ) based kinematics and dynamics are used for the modeling of the relative motions between a chaser satellite… More >

Taku Nonomura

The International Conference on Computational & Experimental Engineering and Sciences, Vol.21, No.4, pp. 73-74, 2019, DOI:10.32604/icces.2019.05266

Abstract In this presentation, a family of Kalman filter dynamic mode decomposition, which consists of algorithms of the linear Kalman filter DMD method which identify the linear system and the extended Kalman filter DMD method which simultaneously identify the system and estimates state variable, is introduced. Then, the application of the extended Kalman filter DMD to data assimilation is discussed. More >

L.C.G. DeSouza¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.5, No.3, pp. 163-172, 2008, DOI:10.3970/icces.2008.005.163

Abstract Satellite Attitude Control System usually does not have all the states available for feedback; therefore, full state estimation by any sort of filtering methodology becomes essential. A good estimation algorithm must filter out the undesirable noise from the measurement signal. Kalman Filter (KF) technique is a traditional procedure to estimate the states of a linear system that are not always measured directly by the sensors, minimizing the variance of the estimated error. However, the KF is not fully robustness proven in face of unpredictable noise sources and it is not always able to minimize the error under severe conditions. In… 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 receiver with the INS data.… More >

Zhimin Chen^1,2, Yuanxin Qu¹, Yuming Bo¹, Yongliang Zhang¹, Bo Cong¹, Xinfeng Yu¹

CMES-Computer Modeling in Engineering & Sciences, Vol.108, No.5, pp. 303-313, 2015, DOI:10.3970/cmes.2015.108.303

Abstract For the sake of a higher accuracy of active aircraft GPS tracking, the tracking algorithm based on pseudo-linear Kalman filter is hereby proposed. This algorithm simplifies geometrical and algebraic relations to obtain a pseudo-linear model, then tracking the target by means of Kalman filter algorithm. Meanwhile, the tracking algorithm is studied to build a velocity & position tracking model and a velocity & acceleration tracking model. As shown by the experimental result, the tracking algorithm based on pseudo-linear Kalman filter can meet the requirement of active aircraft GPS tracking, but also attain a higher tracking accuracy in velocity & acceleration… More >

Hai-Kun Wang^1,2, Robert Haynes³, Hong-Zhong Huang¹, Leiting Dong^2,4, Satya N. Atluri²

CMES-Computer Modeling in Engineering & Sciences, Vol.105, No.1, pp. 1-24, 2015, DOI:10.3970/cmes.2015.105.001

Abstract In this paper, we propose an approach for diagnostics and prognostics of damaged aircraft structures, by combing high-performance fatigue mechanics with filtering theories. Fast & accurate deterministic analyses of fatigue crack propagations are carried out, by using the Finite Element Alternating Method (FEAM) for computing SIFs, and by using the newly developed Moving Least Squares (MLS) law for computing fatigue crack growth rates. Such algorithms for simulating fatigue crack propagations are embedded in the computer program Safe- Flaw, which is called upon as a subroutine within the probabilistic framework of filter theories. Both the extended Kalman as well as particle… More >

M.R. Myers¹, A.B. Jorge², D.E. Yuhas³, D.G. Walker¹

CMES-Computer Modeling in Engineering & Sciences, Vol.83, No.3, pp. 221-248, 2012, DOI:10.3970/cmes.2012.083.221

Abstract An adaptive extended Kalman filter is developed and investigated for a transient heat transfer problem in which a high heat flux spot source is applied on one side of a thin plate and ultrasonic pulse time of flight is measured between spatially separated transducers on the opposite side of the plate. The novel approach is based on the uncertainty in the state model covariance and leverages trends in the extended Kalman filter covariance to drive changes to the state model covariance during convergence. This work is an integral part of an effort to develop a system capable of locating the… More >

Raquel R. Pinho¹, João Manuel R. S. Tavares¹

CMES-Computer Modeling in Engineering & Sciences, Vol.46, No.1, pp. 51-76, 2009, DOI:10.3970/cmes.2009.046.051

Abstract This work addresses the problem of tracking feature points along image sequences. In order to analyze the undergoing movement, an approach based on the Kalman filtering technique has been used, which basically carries out the estimation and correction of the features' movement in every image frame. So as to integrate the measurements obtained from each image into the Kalman filter, a data optimization process has been adopted to achieve the best global correspondence set. The proposed criterion minimizes the cost of global matching, which is based on the Mahalanobis distance. A management model is employed to manage the features being… 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 single point positioning, and the… More >