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A distributed multirate IMM algorithm for multiplatform tracking

MATHEMATICAL AND COMPUTER modelLING 2000年第10期32卷 1095-1116页

作者： Hong, L Ding, Z Wright State Univ Dept Elect Engn Dayton OH 45435 USA

A distributed multirate interacting multiple model (DMRIMM) algorithm for multi-platform tracking is proposed. Under the assumption that each model operates at an update rate proportional to the model's assumed dynamics, a wavelet transform is used to generate equivalent lent multirate measurements and a multirate constant-velocity (MRCV) model is derived. Thus, a multirate interacting multiple model (MRIMM) algorithm using an MRCV model and multirate measurements is obtained. Based on the multirate IMM, its distributed version DMRIMM algorithm for multiplatform tracking is proposed. The MRIMM algorithm is first employed to perform each local/platform estimation. A global filter is then constructed to perform a fusion of MRIMM estimations. The advantages of low computation loads and performance improvement are demonstrated through Monte Carlo simulations. (C) 2000 Elsevier Science Ltd. All rights reserved.

关键词： interacting multiple model algorithm multiplatform tracking distributed system multirate measurement multirate model

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PCRLB-based Optimal Sensor Selection for Maneuvering Target Tracking

PCRLB-based Optimal Sensor Selection for Maneuvering Target ...

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7th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM)

作者： Liu, Zhigang Wang, Jinkuan Northeastern Univ Inst Engn Optimizat & Smart Antenna Qinhuangdao 066004 Peoples R China

ISBN: (纸本)9781424462520

To deal with the problem of tracking a maneuvering target in range-based sensor networks, we firstly derive the multiple model posterior Cramer-Rao lower bound(PCRLB), and on the basis of this bound, choose the sensor subset that may attend the incoming tracking event. Secondly, we design the sensor selection strategy under communication constraint, and further pick up the optimal sensor. Thirdly, we can estimate the state of the maneuvering target by making use of the interacting multiple model(IMM) algorithm. Finally, the simulation results show the effectiveness of the proposed scheme.

关键词： Covariance matrix Equations IMM algorithm Mathematical model PCRLB-based optimal sensor selection Prediction algorithms Radar tracking Signal processing Target tracking interacting multiple model algorithm maneuvering target tracking multiple model posterior Cramer-Rao lower bound optimal sensor range-based sensor networks sensor placement sensor placement target tracking wireless sensor networks wireless sensor networks

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A Fuzzy Adaptive Strong Tracking algorithm with Fading Factor 14

A Fuzzy Adaptive Strong Tracking Algorithm with Fading Facto...

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14th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI)

作者： Fang, Shuai Zhao, Chuchu Sun, Jinping CETC Res Inst 3 Beijing Peoples R China Beihang Univ Sch Elect & Informat Engn Beijing Peoples R China

ISBN: (纸本)9781665400046

The maximum acceleration parameter determines the effect of the current statistical (CS) model. Thus, when tracking weak maneuvering targets or targets whose actual acceleration exceeds the given value, the tracking performance of the traditional algorithm that sets with a priori fixed value will drop sharply. To solve this problem, a fuzzy adaptive strong tracking algorithm with fading factor (IAFCS-IMM) is proposed. The algorithm adopts a two-level fuzzy logic system. Through the first-level fuzzy logic, a maneuvering factor representing the maneuverability of the target is obtained according to the estimated acceleration information of the model, and the maximum acceleration parameter is adaptively modified. The second-level fuzzy logic is adopted to adjust the model update probability of interacting multiple model (IMM) algorithm according to the maneuver factor. Besides, a fading factor is introduced in the filtering process, which can enhance the robustness of the filter to the sharp mutation of the target state. Simulation results demonstrate that IAFCS-IMM algorithm achieves good results in filtering accuracy and tracking stability of maneuvering targets.

关键词： maneuvering target tracking fuzzy logic CS model interacting multiple model algorithm

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IMM algorithm Based on H_∞ Filter for Maneuvering Target Tracking 36

IMM Algorithm Based on <i>H</i><sub>∞</sub> Filter for Mane...

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36th Chinese Control Conference (CCC)

作者： Liu, Meiqin Fan, Zhen Wang, Xie Zhang, Senlin Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Zhejiang Univ Coll Elect Engn Hangzhou 310027 Zhejiang Peoples R China

ISBN: (纸本)9789881563934

Correct knowledge of noise statistics is essential for an effective estimator in maneuvering target tracking. In practice, however, the noise statistics are usually unknown or not perfectly known. To deal with the estimation problem in linear discrete-time systems with Markov jump parameters, where the measurement noise covariance is unknown, a novel approach is presented in this paper. This approach is based on the interacting multiple model (IMM) framework. An H-infinity filter is employed to construct a noise statistics estimator to obtain the information which is necessary for the IMM algorithm. In our approach, even the priori knowledge of noise statistics is not needed. The noise statistics loss problem is solved while the merits of IMM algorithm is reserved. The effectiveness of the proposed approach is demonstrated in comparison with single-model H-infinity filter through Monte Carlo simulation for maneuvering target tracking.

关键词： State Estimation Noise Statistics Estimate H-infinity Filter interacting multiple model algorithm Target Tracking

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A Modified Tracking algorithm for NSHV Based on Aerodynamic model

A Modified Tracking Algorithm for NSHV Based on Aerodynamic ...

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2021 CIE International Conference on Radar, Radar 2021

作者： Zhang, Jiaqi Zheng, Jibin Sun, Dianxing Liu, Hongwei Xidian University National Laboratory of Rader Signal Processing Xian China China Electronic Technology Group Corporation Science and Technology on Electronic Test and Measurement Laboratory Qingdao China

ISBN: (纸本)9781665498142

In order to track the near space hypersonic vehicle (NSHV), we propose a tracking model containing aerodynamic and kinematic information using interacting multiple model (IMM) algorithm with accruate speed prior information. Because traditional maneuver models are difficult to describe the complex movement characteristics, which involves large-scale high-speed mobile, large flight cover, etc., fault-acceleration model with surface damage model and external disturbance model are proposed. With the model, the state equations are constructed and the system dynamic error is deduced taking variable structure multiple model (VSMM) algorithm as the flitering algorithm. Moreover, an adaptive method for the change of control variables is proposed for setting parameters apporiately in the situations when a prior information is unknown. Simulation experiments are conducted to validate the superiorities among all tracking algorithms in this paper. © 2021 IEEE.

关键词： aerodynamic model interacting multiple model algorithm near space hypersonic vehicle tracking

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Channel tracking of uncoordinated access under uncertain evolution for massive connectivity with massive MIMO

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AEU-INTERNATIONAL JOURNAL OF ELECTRONICS AND COMMUNICATIONS 2021年 141卷

作者： Soltanizadeh, Hediyeh Falahati, Abolfazl Iran Univ Sci & Technol IUST Dept Elect Engn Tehran Iran

Massive MIMO technologies are a major candidate to serve high-rate Internet of Things (IoT) with moving or motionless devices if all channels of devices are known to BS. In this paper, an unknown dynamical model for channel evolution is assumed over time, and regardless of whether devices send pilots or not, joint channel estimation and tracking are investigated. At first, a new suboptimal tracker, Uncertain interacting multiple model (UIMM), is derived for the coordinated access. We define a new setup, referred to as an uncoordinated access, in which many devices with an unknown probabilities access BS without coordination. Then, three novel suboptimal trackers are designed based on UIMM for this uncoordinated access. To decrease computational complexity of the designed trackers, two schemes are applied. The Mean Square Error (MSE) gap between the mentioned scenario and the previous uncoordinated access is computed theoretically and represented by simulation results. Also, a new fundamental limit is defined which is referred to as Cost of Uncoordinated Access under Uncertain Channels (CUAUC). The CUAUC is used to evaluate the MSE gap between the optimal coordinated tracker and the designed suboptimal uncoordinated trackers. Finally, the CUAUC and the efficiency of the designed trackers are evaluated via simulations.

关键词： Uncoordinated access Internet of things Massive MIMO Channel tracking interacting multiple model algorithm Channel aging

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Adaptive Tracking Method of Distorted Voltage Using IMM algorithm under Grid Frequency Fluctuation Conditions

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ENERGIES 2021年第23期14卷 7944-7944页

作者： Nie, Haoyao Nie, Xiaohua Nanchang Univ Sch Econ & Management Nanchang 330031 Jiangxi Peoples R China Univ Manitoba IH Asper Sch Business Winnipeg MB R3T 5V4 Canada Nanchang Univ Dept Energy & Elect Engn Nanchang 330031 Jiangxi Peoples R China

This paper newly proposes an interactive multiple model (IMM) algorithm to adaptively track distorted AC voltage with the grid frequency fluctuation. The usual tracking methods are Kalman filter (KF) algorithm with a fixed frequency and KF algorithm with frequency identifier. The KF algorithm with a fixed frequency has a larger covariance parameter to guarantee the tracking robustness. However, it has a large tracking error. The KF algorithm with frequency identifier overly depends on the accuracy and stability of frequency identifier. The advantage of the proposed method is that it is decoupled from frequency detection and does not depend on frequency detection accuracy. First, the orthogonal vector dynamic (OVD) tracking model of the sine wave is established. Then, a model set covering the grid frequency fluctuation range is formed, and a new OVD-IMM tracking algorithm is proposed in combination with IMM algorithm. In the end, the effectiveness and accuracy of the proposed OVD-IMM algorithm are verified through simulations and experiments.

关键词： frequency fluctuation distorted voltage Kalman filter dynamic tracking model interacting multiple model algorithm

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The IMM Approach to the Fault Detection Problem

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IFAC Proceedings Volumes 1997年第11期30卷 603-608页

作者： Murat Efe Derek P. Atherton School of Engineering University of Sussex Falmer Brighton BN1 9QT UK

An observer-based fault detection scheme utilizing the interacting multiple model ( IMM ) approach is presented for an industrial actuator benchmark problem. The requirement is to detect current and position faults in a brushless D.C. motor which is subject to both actuator and sensor faults in the presence of unknown load torques. Fault detection is carried out by threshold checking on the model probabilties calculated by the algorithm. The proposed scheme has been applied to the given benchmark data with current and position fault detection achieved in a good detection time and with a high detection probabilty, regardless of the load torque.

关键词： Fault detection interacting multiple model algorithm state estimation Kalman filters

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Anti-ship Missile Trajectory Tracking Based on CS_UKF And interacting multiple models 33

Anti-ship Missile Trajectory Tracking Based on CS_UKF And In...

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33rd Chinese Control Conference (CCC)

作者： Xu Tian Ye Xu Xue Song East China Jiaotong Univ Elect Coll Nanchang 330013 Peoples R China

ISBN: (纸本)9781479947249

Anti-ship missile is a kind of typical high maneuvering target which has the characteristics of strong motor and multiple mobile. Especially its unique form of "snake maneuver" brought great difficulties to the tracking system. This article used the IMM algorithm and the "current" statistical model constituted model set, together with the method of UKF filter which avoid extended kalman tedious Jacobi matrix calculation, then we get a new method for anti-ship missiles tracking. Results show that the method has good tracking performance to strong maneuvering target just like anti-ship missile.

关键词： Anti-ship missile tracking Current statistic model UKF interacting multiple model algorithm

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IMM algorithm Based on H∞ Filter for Maneuvering Target Tracking

IMM Algorithm Based on H∞ Filter for Maneuvering Target Tra...

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第36届中国控制会议

作者： Meiqin Liu Zhen Fan Xie Wang Senlin Zhang State Key Laboratory of Industrial Control Technology Zhejiang University College of Electrical Engineering Zhejiang University

Correct knowledge of noise statistics is essential for an effective estimator in maneuvering target *** practice,however,the noise statistics are usually unknown or not perfectly *** deal with the estimation problem in linear discretetime systems with Markov jump parameters,where the measurement noise covariance is unknown,a novel approach is presented in this *** approach is based on the interacting multiple model(IMM) *** H Alter is employed to construct a noise statistics estimator to obtain the information which is necessary for the IMM *** our approach,even the priori knowledge of noise statistics is not *** noise statistics loss problem is solved while the merits of IMM algorithm is *** effectiveness of the proposed approach is demonstrated in comparison with single-model H Alter through Monte Carlo simulation for maneuvering target tracking.

关键词： State Estimation Noise Statistics Estimate H∞ Filter interacting multiple model algorithm Target Tracking

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