Equality Constrained Robust Measurement Fusion for Adaptive Kalman-Filter-Based Heterogeneous Multi-Sensor Navigation

Zhou, Zebo; Li, Yong; Liu, Junning; Li, Gun

doi:10.1109/taes.2014.6619919

Cited by 29 publications

(36 citation statements)

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“…In fact, by using inertial sensors, the object's motion can be computed with much simpler frameworks. These years the attitude and position estimation based on MEMS sensors have been extensively studied [22], which provides us with new ways of obtaining hand's motion [23].…”

Section: Introductionmentioning

confidence: 99%

Effective Inertial Hand Gesture Recognition Using Particle Filtering Based Trajectory Matching

Wang

Chen

2018

Journal of Electrical and Computer Engineering

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Hand gesture recognition has become more and more popular in applications like intelligent sensing, robot control, smart guidance, and so on. In this paper, an inertial sensor based hand gesture recognition method is proposed. The proposed method obtains the trajectory of the hand by using a position estimator. The proposed method utilizes the attitude estimation to produce velocity and position estimation. A particle filter (PF) is employed to estimate the attitude quaternion from gyroscope, accelerometer, and magnetometer sensors. The improvement is based on the resampling method making the original filter much faster to converge. After smoothing, the trajectory is then converted to low-definition images which are further sent to a backpropagation neural network (BP-NN) based recognizer for matching. Experiments on real-world hardware are carried out to show the effectiveness and uniqueness of the proposed method. Compared with representative methods using accelerometer or vision sensors, the proposed method is proved to be fast, reliable, and accurate.

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Section: Introductionmentioning

confidence: 99%

Effective Inertial Hand Gesture Recognition Using Particle Filtering Based Trajectory Matching

Wang

Chen

2018

Journal of Electrical and Computer Engineering

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“…Integrated navigation technology can greatly improve the reliability and the precise of navigation system [1]. For the GNSS multi-constellation navigation system, because the four satellite navigation systems (GPS, GLONASS, Galileo signal, and Beidou) have different signal characteristics, including modulation mode, carrier frequency, and the generation of pseudo random noise code (PRN) code, making the consideration between the four satellite systems compatibility and interoperability is very important in the design of the GNSS receiver [2].…”

Section: Introductionmentioning

confidence: 99%

Research on multi-constellation GNSS compatible acquisition strategy based on GPU high-performance operation

Guo

Zhong

2018

J Wireless Com Network

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With the continuous development of satellite navigation, how to make full use of the compatibility and interoperability among the four constellations deserves our deep thinking. Signal acquisition is a critical technology that affects the performance of GNSS receivers. However, its implementation has high requirements on both resource consumption and processing time. In recent years, graphics processing unit (GPU) technology with a large number of parallel processing units is gradually applied to the navigation field. In this paper, a multi-constellation-compatible capture strategy based on GPU is proposed. Compared with the traditional GNSS signal processing, the design has better flexibility and portability, and the acquisition parameters of the system can be configured flexibly through the interface. The experimental results show that the proposed scheme makes full use of the powerful parallel processing capability of GPU, which greatly reduces the acquisition time and improves the efficiency of signal processing, with the increase of data processing. In addition, as the amount of signal processing data increases, the advantages of the CPU highperformance computing platform will be more obvious.

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“…[9][10][11][12][13] While in several real-world scenarios, some agents may collaborate while others compete. [14][15][16][17][18][19][20][21][22][23][24][25] As far as we know, less attention has been paid to these antagonistic networks in multi-agent systems. Antagonistic interactions are represented as signed graphs, that is, graphs which can assume also as negative weights.…”

Section: Introductionmentioning

confidence: 99%

Formation behaviors of networks with antagonistic interactions of agents

Zou

2017

International Journal of Distributed Sensor Networks

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In this study, a new formation behavior problem for second-order multi-agent systems with time delay is investigated in the presence of antagonistic interactions. We first proposed a formation behavior protocol with time delay for each agent in the antagonistic network. Then, by a frequency-domain analysis, a sufficient and necessary condition is derived to guarantee the consensus stability of the multi-agent system. It is shown that the agents in the same group form their own desired formation while keeping a desired relative position with other groups. Finally, numerical simulations are provided to illustrate the obtained results.

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Equality Constrained Robust Measurement Fusion for Adaptive Kalman-Filter-Based Heterogeneous Multi-Sensor Navigation

Cited by 29 publications

References 0 publications

Effective Inertial Hand Gesture Recognition Using Particle Filtering Based Trajectory Matching

Effective Inertial Hand Gesture Recognition Using Particle Filtering Based Trajectory Matching

Research on multi-constellation GNSS compatible acquisition strategy based on GPU high-performance operation

Formation behaviors of networks with antagonistic interactions of agents

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