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Zhang Y.,Northwestern Polytechnical University | Zhang Y.,Key Laboratory of Information Fusion Technology LIFT | Chen K.,Rutgers University | Yi J.,Rutgers University | And 2 more authors.
IEEE/ASME Transactions on Mechatronics

Tracking whole-body human pose in physical human-machine interactions is challenging because of highly dimensional human motions and lack of inexpensive, nonintrusive motion sensors in outdoor environment. In this paper, we present a computational scheme to estimate the human whole-body pose with application to bicycle riding using a small set of wearable sensors. The estimation scheme is built on the fusion of gyroscopes, accelerometers, force sensors, and physical rider-bicycle interaction constraints through an extended Kalman filter design. The use of physical rider-bicycle interaction constraints helps not only eliminate the integration drifts of inertial sensor measurements but also reduce the number of the needed wearable sensors for pose estimation. For each set of the upper and the lower limb, only one tri-axial gyroscope is needed to accurately obtain the 3-D pose information. The drift-free, reliable estimation performance is demonstrated through both indoor and outdoor riding experiments. © 1996-2012 IEEE. Source

Xu J.,Xian Jiaotong University | Lv G.,Xian Jiaotong University | Zhang C.,Xian Jiaotong University | Zhang Y.,Key Laboratory of Information Fusion Technology LIFT | Zhang Y.,Northwestern Polytechnical University
IET Communications

In this study, the authors present a novel low backhaul load cooperative transmission framework for the two-cell multiple-input-single-output systems. In this framework, the neighbouring two base stations (BSs) take turns to transmit data in two consecutive slots. In each slot, only one BS is active, transmitting the preprocessed data symbols of both its own serving user and the cooperative user in neighbouring cell, and sharing its preprocessed data symbols to the other cooperative BS for next transmission. Linear constellation spreading is utilised for preprocessing which helps the system to exploit the macro-diversity without reducing the multiplexing gain. Besides, zero-forcing beamforming is applied in each transmission slot so as to cancel the multiuser interference. In this way, the inter-cell links become beneficial rather than detrimental. Pairwise error probability analysis demonstrates that the multi-cell spatial diversity gain can be achieved for each data stream. Both theoretical analysis and simulation results confirm that the proposed scheme outperforms the existing relevant strategies with less channel estimation overhead. It is shown that because of the higher diversity order it achieved, the proposed scheme can significantly improve the error performance in a distributed manner while maintaining the same multiplexing gain. © The Institution of Engineering and Technology 2014. Source

Wang X.,Northwestern Polytechnical University | Wang X.,Key Laboratory of Information Fusion Technology LIFT | Liang Y.,Northwestern Polytechnical University | Liang Y.,Key Laboratory of Information Fusion Technology LIFT | And 6 more authors.
IEEE Transactions on Automatic Control

This paper is concerned with the Gaussian approximation (GA) smoothing estimation for the nonlinear system with the colored measurement noise modeled as an autoregressive process. Firstly, based on measurement differencing scheme, designing the GA smoothers with the colored measurement noise is transformed into deriving the GA ones with delayed state. Secondly, the novel fixed- interval, fixed-point and fixed-lag GA smoothers are proposed via the recursive operation of analytical computation and nonlinear integrals, as the general and unifying frameworks: they are applicable for both linear and nonlinear systems; by setting the noise correlation parameter as zero, they can automatically reduce to the standard GA smoothers with uncorrelated white noises; many implementations of the GA frameworks can be developed through utilizing different numerical technologies for computing such nonlinear integrals, e.g., the cubature rule based cubature Kalman smoothers (CKSs) with the colored measurement noise. Finally, the superior performance in estimation accuracy and computation efficiency of the proposed smoothing methods is demonstrated with a multi-sensor target tracking example. © 2014 IEEE. Source

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