Noise-aware manoeuvring target tracking algorithm in wireless sensor networks by a novel adaptive cubature Kalman filter
Current target tracking algorithms for wireless sensor networks in noise environments have large positioning errors. Owing to the environmental noise, Kalman filters (KFs) are used to estimate the target position. To reduce the adverse effect of unknown or time-varying noise on KFs, adaptive KFs (AK...
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| Vydáno v: | IET radar, sonar & navigation Ročník 14; číslo 11; s. 1795 - 1802 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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The Institution of Engineering and Technology
01.11.2020
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| ISSN: | 1751-8784, 1751-8792 |
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| Abstract | Current target tracking algorithms for wireless sensor networks in noise environments have large positioning errors. Owing to the environmental noise, Kalman filters (KFs) are used to estimate the target position. To reduce the adverse effect of unknown or time-varying noise on KFs, adaptive KFs (AKFs) are developed. However, the present AKFs can only achieve second-order estimation accuracy. To improve the existing target tracking algorithm's positioning accuracy under unknown and time-varying noise environments, the authors propose a noise-aware algorithm based on a novel third-order adaptive cubature KF (ACKF) with higher estimation accuracy, which improves the accuracy of the existing algorithm by up to 63%. The innovative ACKF contains a new third-order noise statistic estimator and a traditional cubature KF without noise perception. A large number of numerical simulations and practical experiments show that the proposed noise-aware target tracking algorithm based on the novel ACKF is always more accurate than the target tracking algorithms based on the current KFs, no matter whether the moving target is manoeuvring or not, whether the strength of the noise is small or large, whether the number of anchor nodes is many or few, and whether the noise is time-varying or constant. |
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| AbstractList | Current target tracking algorithms for wireless sensor networks in noise environments have large positioning errors. Owing to the environmental noise, Kalman filters (KFs) are used to estimate the target position. To reduce the adverse effect of unknown or time-varying noise on KFs, adaptive KFs (AKFs) are developed. However, the present AKFs can only achieve second-order estimation accuracy. To improve the existing target tracking algorithm's positioning accuracy under unknown and time-varying noise environments, the authors propose a noise-aware algorithm based on a novel third-order adaptive cubature KF (ACKF) with higher estimation accuracy, which improves the accuracy of the existing algorithm by up to 63%. The innovative ACKF contains a new third-order noise statistic estimator and a traditional cubature KF without noise perception. A large number of numerical simulations and practical experiments show that the proposed noise-aware target tracking algorithm based on the novel ACKF is always more accurate than the target tracking algorithms based on the current KFs, no matter whether the moving target is manoeuvring or not, whether the strength of the noise is small or large, whether the number of anchor nodes is many or few, and whether the noise is time-varying or constant. |
| Author | Fang, Xuming Chen, Lijun |
| Author_xml | – sequence: 1 givenname: Xuming surname: Fang fullname: Fang, Xuming email: fangxm@smail.nju.edu.cn organization: 1School of Software Engineering, Jinling Institute of Technology, Nanjing, People's Republic of China – sequence: 2 givenname: Lijun surname: Chen fullname: Chen, Lijun organization: 2Department of Computer Science and Technology, Nanjing University, Nanjing, People's Republic of China |
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| Cites_doi | 10.1016/j.comcom.2006.12.020 10.1109/TAES.2017.2756763 10.1109/CCSSE.2014.7224505 10.1007/s12083-015-0372-9 10.1002/0470045345 10.1109/ROBOT.2008.4543780 10.1016/j.adhoc.2017.11.008 10.30684/etj.34.15A.15 10.1109/ICMA.2017.8016075 10.1109/JSEN.2015.2510020 10.1109/C-CODE.2017.7918918 10.3390/s18020332 10.1109/TSP.2007.906770 10.1109/JSEN.2019.2941273 10.1109/INFCOMW.2018.8406856 10.1049/iet-rsn.2014.0533 10.1016/j.compeleceng.2017.12.036 10.1109/LCOMM.2017.2765642 10.1109/KCIC.2016.7883626 10.1109/WiSPNET.2016.7566539 10.3390/s18124335 10.1007/978-981-10-6544-6_12 10.3390/app9091916 10.1109/WiMob.2009.30 10.3390/s16060805 10.1109/TAC.2017.2730480 10.1002/acs.2467 10.1109/JSEN.2018.2873357 10.1109/LWC.2017.2762305 10.1109/DISCOVER.2016.7806221 10.1109/TIT.2017.2693180 10.3390/s19061371 10.1109/TII.2019.2909135 10.1016/j.asr.2014.12.005 10.1016/j.actaastro.2015.12.014 10.1109/JSEN.2019.2892652 10.1016/j.egypro.2018.09.204 10.1109/ICACDOT.2016.7877655 10.1109/ICMA.2017.8016115 10.1109/ICCAS.2015.7364990 10.1109/INDIN.2017.8104800 10.1016/j.comcom.2016.10.011 10.14257/ijsh.2015.9.5.19 10.1088/1742-6596/1325/1/012171 10.1109/LSP.2017.2724848 |
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| Keywords | existing target tracking algorithm noise-aware target tracking algorithm wireless sensor networks moving target noise-aware manoeuvring target tracking algorithm noise environments current target tracking algorithms environmental noise higher estimation accuracy tracking filters noise perception target position third-order noise statistic estimator adaptive KF second-order estimation accuracy third-order adaptive cubature KF noise-aware algorithm positioning errors target tracking adaptive Kalman filters numerical analysis time-varying novel adaptive cubature Kalman filter Kalman filters |
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| References | Jondhale, S.R.; Deshpande, R.S. (C12) 2018; 19 Mohammed, S.L. (C46) 2016; 34 Xile, D.; Caiping, Z.; Jiuchun, J. (C36) 2018; 152 Zhu, W.; Wang, W.; Yuan, G. (C33) 2016; 16 Narasimhappa, M.; Mahindrakar, A.D.; Guizilini, V.C. (C41) 2019; 20 Yang, D.; Xu, B.; Rao, K. (C6) 2018; 18 Ciuonzo, D.; Rossi, P.S. (C49) 2017; 7 Ahmadi, H.; Viani, F.; Bouallegue, R. (C3) 2018; 70 Huang, Y.; Zhang, Y.; Wu, Z. (C15) 2017; 63 Assa, A.; Plataniotis, K.N. (C16) 2017; 24 Zhu, L.; Cheng, X. (C44) 2015; 9 Huang, Y.; Zhang, Y.; Xu, B. (C17) 2017; 54 Sun, Y.; Zhang, F.; Wan, Q. (C30) 2019; 19 Shi, Y.; Tang, X.; Feng, X. (C40) 2018; 18 El Amine, C.M.; Mohamed, O.; Boualam, B. (C45) 2016; 9 Meng, Y.; Gao, S.; Zhong, Y. (C14) 2016; 120 Baronti, P.; Pillai, P.; Chook, V.W. (C8) 2007; 30 Zhou, B.; Chen, Q.; Xiao, P. (C7) 2017; 63 Huang, T.; Jiang, H.; Zou, Z. (C34) 2019; 9 Gao, S.; Hu, G.; Zhong, Y. (C37) 2015; 29 Wu, M.; Xiong, N.; Tan, L. (C19) 2019; 15 Zhang, J.; Li, H.; Li, J. (C25) 2015; 8 Fang, X.; Jiang, Z.; Nan, L. (C43) 2017; 101 Mahfouz, S.; Mourad-Chehade, F.; Honeine, P. (C9) 2015; 16 Liu, X.; Jiang, S. (C32) 2013; 153 Sharma, G.; Kumar, A. (C22) 2018; 72 Guo, H.; Guo, J.; Yu, M. (C35) 2015; 55 Kim, J.S.; Lee, H.J.; Oh, R.D. (C5) 2015; 9 Ge, B.; Zhang, H.; Jiang, L. (C18) 2019; 19 Ke, M.; Xu, Y.; Anpalagan, A. (C28) 2017; 22 Niu, R.; Varshney, P.K. (C48) 2007; 56 December 2014 2017; 7 2017; 63 2019; 9 2015; 16 October 2009 September 2016 May 2008 August 2017 2017; 22 August 2016 2017; 24 2019; 15 2015; 55 2009 2019; 19 2006 November 2016 May 2017 2007; 30 2015; 9 2015; 8 2016; 16 2007; 56 2016; 120 2016; 34 2018; 19 2018; 152 July 2011 2018; 18 October 2015 March 2016 October 2019 March 2017 2015; 29 2019; 20 July 2017 2017; 54 April 2018 2018; 70 2018; 72 2013; 153 2017; 101 February 2009 2016; 9 e_1_2_8_28_1 e_1_2_8_24_1 e_1_2_8_49_1 e_1_2_8_5_1 e_1_2_8_7_1 e_1_2_8_9_1 e_1_2_8_20_1 e_1_2_8_43_1 e_1_2_8_22_1 e_1_2_8_45_1 Grilo A. (e_1_2_8_53_1) 2009 e_1_2_8_41_1 e_1_2_8_17_1 e_1_2_8_19_1 e_1_2_8_13_1 e_1_2_8_36_1 e_1_2_8_15_1 e_1_2_8_38_1 Zhang J. (e_1_2_8_26_1) 2015; 8 e_1_2_8_32_1 e_1_2_8_11_1 e_1_2_8_34_1 e_1_2_8_51_1 e_1_2_8_30_1 Xiao J. (e_1_2_8_48_1) 2019 e_1_2_8_29_1 e_1_2_8_46_1 e_1_2_8_27_1 e_1_2_8_2_1 e_1_2_8_4_1 e_1_2_8_6_1 e_1_2_8_8_1 e_1_2_8_21_1 e_1_2_8_42_1 e_1_2_8_23_1 e_1_2_8_44_1 Mohammed S.L. (e_1_2_8_47_1) 2016; 34 e_1_2_8_40_1 Ciuonzo D. (e_1_2_8_54_1) 2011 e_1_2_8_18_1 e_1_2_8_39_1 e_1_2_8_14_1 e_1_2_8_35_1 e_1_2_8_16_1 e_1_2_8_37_1 Sun X. (e_1_2_8_3_1) 2016 Liu X. (e_1_2_8_33_1) 2013; 153 Arasaratnam I. (e_1_2_8_52_1) 2009 e_1_2_8_10_1 e_1_2_8_31_1 e_1_2_8_12_1 Yu X. (e_1_2_8_25_1) 2017 e_1_2_8_50_1 |
| References_xml | – volume: 34 start-page: 2950 issue: 15 year: 2016 end-page: 2959 ident: C46 article-title: Distance estimation based on RSSI and log-normal shadowing models for ZigBee wireless sensor network publication-title: Eng. Technol. J. – volume: 120 start-page: 171 year: 2016 end-page: 181 ident: C14 article-title: Covariance matching based adaptive unscented Kalman filter for direct filtering in INS/GNSS integration publication-title: Acta Astronaut. – volume: 63 start-page: 594 issue: 2 year: 2017 end-page: 601 ident: C15 article-title: A novel adaptive Kalman filter with inaccurate process and measurement noise covariance matrices publication-title: IEEE Trans. Autom. Control – volume: 18 start-page: 4335 issue: 12 year: 2018 ident: C40 article-title: Hybrid adaptive cubature Kalman filter with unknown variance of measurement noise publication-title: Sensors – volume: 20 start-page: 250 issue: 1 year: 2019 end-page: 260 ident: C41 article-title: MEMS based IMU drift minimization: Sage Husa adaptive robust Kalman filtering publication-title: IEEE Sens. J. – volume: 18 start-page: 332 issue: 2 year: 2018 ident: C6 article-title: Passive infrared (PIR)-based indoor position tracking for smart homes using accessibility maps and a-star algorithm publication-title: Sensors – volume: 24 start-page: 1288 issue: 9 year: 2017 end-page: 1292 ident: C16 article-title: Adaptive Kalman filtering by covariance sampling publication-title: IEEE Signal Process. Lett. – volume: 8 start-page: 109 issue: 1 year: 2015 end-page: 116 ident: C25 article-title: An improved CPE localization algorithm for wireless sensor networks publication-title: Int. J. Future Gen. Commun. Netw. – volume: 70 start-page: 14 year: 2018 end-page: 22 ident: C3 article-title: An accurate prediction method for moving target localization and tracking in wireless sensor networks publication-title: Ad Hoc Netw. – volume: 9 start-page: 195 issue: 5 year: 2015 end-page: 204 ident: C5 article-title: Smart integrated multiple tracking system development for IoT based target-oriented logistics location and resource service publication-title: Int. J. Smart Home – volume: 30 start-page: 1655 issue: 7 year: 2007 end-page: 1695 ident: C8 article-title: Wireless sensor networks: a survey on the state of the art and the 802.15. 4 and ZigBee standards publication-title: Comput. Commun. – volume: 29 start-page: 201 issue: 2 year: 2015 end-page: 223 ident: C37 article-title: Windowing and random weighting-based adaptive unscented Kalman filter publication-title: Int. J. Adapt. Control Signal Process. – volume: 55 start-page: 1470 issue: 5 year: 2015 end-page: 1476 ident: C35 article-title: A weighted combination filter with nonholonomic constrains for integrated navigation systems publication-title: Adv. Space Res. – volume: 19 start-page: 224 issue: 1 year: 2018 end-page: 233 ident: C12 article-title: Kalman filtering framework-based real time target tracking in wireless sensor networks using generalized regression neural networks publication-title: IEEE Sens. J. – volume: 22 start-page: 316 issue: 2 year: 2017 end-page: 319 ident: C28 article-title: Distributed TOA-based positioning in wireless sensor networks: a potential game approach publication-title: IEEE Commun. Lett. – volume: 9 start-page: 1916 issue: 9 year: 2019 ident: C34 article-title: An integrated adaptive Kalman filter for high-speed UAVs publication-title: Appl. Sci. – volume: 72 start-page: 808 year: 2018 end-page: 827 ident: C22 article-title: Improved range-free localization for three-dimensional wireless sensor networks using genetic algorithm publication-title: Comput. Electr. Eng. – volume: 7 start-page: 162 issue: 2 year: 2017 end-page: 165 ident: C49 article-title: Quantizer design for generalized locally optimum detectors in wireless sensor networks publication-title: IEEE Wirel. Commun. Lett. – volume: 16 start-page: 2115 issue: 7 year: 2015 end-page: 2126 ident: C9 article-title: Non-parametric and semi-parametric RSSI/distance modeling for target tracking in wireless sensor networks publication-title: IEEE Sens. J. – volume: 56 start-page: 339 issue: 1 year: 2007 end-page: 349 ident: C48 article-title: Performance analysis of distributed detection in a random sensor field publication-title: IEEE Trans. Signal Process – volume: 54 start-page: 353 issue: 1 year: 2017 end-page: 368 ident: C17 article-title: A new adaptive extended Kalman filter for cooperative localization publication-title: IEEE Trans. Aerosp. Electron. Syst. – volume: 9 start-page: 795 issue: 4 year: 2016 end-page: 808 ident: C45 article-title: The implementation of indoor localization based on an experimental study of RSSI using a wireless sensor network publication-title: Peer Peer Netw. Appl. – volume: 19 start-page: 1371 issue: 6 year: 2019 ident: C18 article-title: Adaptive unscented Kalman filter for target tracking with unknown time-varying noise covariance publication-title: Sensors – volume: 63 start-page: 3983 issue: 6 year: 2017 end-page: 4007 ident: C7 article-title: The error propagation analysis of the received signal strength-based simultaneous localization and tracking in wireless sensor networks publication-title: IEEE Trans. Inf. Theory – volume: 15 start-page: 5919 issue: 11 year: 2019 end-page: 5930 ident: C19 article-title: Adaptive range-based target localization using diffusion Gauss–Newton method in industrial environments publication-title: IEEE Trans Ind. Inf. – volume: 9 start-page: 1078 issue: 8 year: 2015 end-page: 1087 ident: C44 article-title: High manoeuvre target tracking in coordinated turns publication-title: IET Radar Sonar Navig. – volume: 16 start-page: 805 issue: 6 year: 2016 ident: C33 article-title: An improved interacting multiple model filtering algorithm based on the cubature Kalman filter for maneuvering target tracking publication-title: Sensors – volume: 19 start-page: 3741 issue: 10 year: 2019 end-page: 3750 ident: C30 article-title: Wireless sensor network-based localization method using TDOA measurements in MPR publication-title: IEEE Sens. J. – volume: 101 start-page: 57 year: 2017 end-page: 68 ident: C43 article-title: Noise-aware localization algorithms for wireless sensor networks based on multidimensional scaling and adaptive Kalman filtering publication-title: Comput. Commun. – volume: 153 start-page: 13 issue: 6 year: 2013 end-page: 21 ident: C32 article-title: Research on target tracking based on unscented Kalman filter publication-title: Sens. Transducers – volume: 152 start-page: 520 year: 2018 end-page: 525 ident: C36 article-title: Evaluation of SOC estimation method based on EKF/AEKF under noise interference publication-title: Energy Procedia – volume: 9 start-page: 195 issue: 5 year: 2015 end-page: 204 article-title: Smart integrated multiple tracking system development for IoT based target‐oriented logistics location and resource service publication-title: Int. J. Smart Home – year: 2009 – start-page: 369 year: July 2017 end-page: 374 – start-page: 1709 year: August 2017 end-page: 1713 – volume: 15 start-page: 5919 issue: 11 year: 2019 end-page: 5930 article-title: Adaptive range‐based target localization using diffusion Gauss–Newton method in industrial environments publication-title: IEEE Trans Ind. Inf. – volume: 19 start-page: 3741 issue: 10 year: 2019 end-page: 3750 article-title: Wireless sensor network‐based localization method using TDOA measurements in MPR publication-title: IEEE Sens. J. – volume: 56 start-page: 339 issue: 1 year: 2007 end-page: 349 article-title: Performance analysis of distributed detection in a random sensor field publication-title: IEEE Trans. Signal Process – volume: 54 start-page: 353 issue: 1 year: 2017 end-page: 368 article-title: A new adaptive extended Kalman filter for cooperative localization publication-title: IEEE Trans. Aerosp. Electron. Syst. – start-page: 1 year: July 2011 end-page: 8 – volume: 18 start-page: 332 issue: 2 year: 2018 article-title: Passive infrared (PIR)‐based indoor position tracking for smart homes using accessibility maps and a‐star algorithm publication-title: Sensors – volume: 7 start-page: 162 issue: 2 year: 2017 end-page: 165 article-title: Quantizer design for generalized locally optimum detectors in wireless sensor networks publication-title: IEEE Wirel. Commun. Lett. – start-page: 479 year: November 2016 end-page: 492 – volume: 30 start-page: 1655 issue: 7 year: 2007 end-page: 1695 article-title: Wireless sensor networks: a survey on the state of the art and the 802.15. 4 and ZigBee standards publication-title: Comput. Commun. – volume: 9 start-page: 795 issue: 4 year: 2016 end-page: 808 article-title: The implementation of indoor localization based on an experimental study of RSSI using a wireless sensor network publication-title: Peer Peer Netw. Appl. – start-page: 391 year: February 2009 end-page: 400 – start-page: 40 year: December 2014 end-page: 44 – volume: 22 start-page: 316 issue: 2 year: 2017 end-page: 319 article-title: Distributed TOA‐based positioning in wireless sensor networks: a potential game approach publication-title: IEEE Commun. Lett. – volume: 9 start-page: 1916 issue: 9 year: 2019 article-title: An integrated adaptive Kalman filter for high‐speed UAVs publication-title: Appl. Sci. – start-page: 123 year: October 2009 end-page: 128 – start-page: 594 year: September 2016 end-page: 598 – volume: 24 start-page: 1288 issue: 9 year: 2017 end-page: 1292 article-title: Adaptive Kalman filtering by covariance sampling publication-title: IEEE Signal Process. Lett. – start-page: 211 year: August 2016 end-page: 215 – start-page: 609 year: October 2015 end-page: 613 – start-page: 1942 year: August 2017 end-page: 1946 – volume: 63 start-page: 3983 issue: 6 year: 2017 end-page: 4007 article-title: The error propagation analysis of the received signal strength‐based simultaneous localization and tracking in wireless sensor networks publication-title: IEEE Trans. Inf. Theory – volume: 70 start-page: 14 year: 2018 end-page: 22 article-title: An accurate prediction method for moving target localization and tracking in wireless sensor networks publication-title: Ad Hoc Netw. – volume: 9 start-page: 1078 issue: 8 year: 2015 end-page: 1087 article-title: High manoeuvre target tracking in coordinated turns publication-title: IET Radar Sonar Navig. – volume: 63 start-page: 594 issue: 2 year: 2017 end-page: 601 article-title: A novel adaptive Kalman filter with inaccurate process and measurement noise covariance matrices publication-title: IEEE Trans. Autom. Control – volume: 153 start-page: 13 issue: 6 year: 2013 end-page: 21 article-title: Research on target tracking based on unscented Kalman filter publication-title: Sens. Transducers – volume: 120 start-page: 171 year: 2016 end-page: 181 article-title: Covariance matching based adaptive unscented Kalman filter for direct filtering in INS/GNSS integration publication-title: Acta Astronaut. – start-page: 2233 year: March 2016 end-page: 2237 – start-page: 60 year: November 2016 end-page: 66 – volume: 19 start-page: 224 issue: 1 year: 2018 end-page: 233 article-title: Kalman filtering framework‐based real time target tracking in wireless sensor networks using generalized regression neural networks publication-title: IEEE Sens. J. – volume: 152 start-page: 520 year: 2018 end-page: 525 article-title: Evaluation of SOC estimation method based on EKF/AEKF under noise interference publication-title: Energy Procedia – volume: 101 start-page: 57 year: 2017 end-page: 68 article-title: Noise‐aware localization algorithms for wireless sensor networks based on multidimensional scaling and adaptive Kalman filtering publication-title: Comput. Commun. – volume: 16 start-page: 2115 issue: 7 year: 2015 end-page: 2126 article-title: Non‐parametric and semi‐parametric RSSI/distance modeling for target tracking in wireless sensor networks publication-title: IEEE Sens. J. – volume: 16 start-page: 805 issue: 6 year: 2016 article-title: An improved interacting multiple model filtering algorithm based on the cubature Kalman filter for maneuvering target tracking publication-title: Sensors – volume: 55 start-page: 1470 issue: 5 year: 2015 end-page: 1476 article-title: A weighted combination filter with nonholonomic constrains for integrated navigation systems publication-title: Adv. Space Res. – start-page: 117 year: May 2017 end-page: 127 – start-page: 144 year: March 2017 end-page: 147 – volume: 34 start-page: 2950 issue: 15 year: 2016 end-page: 2959 article-title: Distance estimation based on RSSI and log‐normal shadowing models for ZigBee wireless sensor network publication-title: Eng. Technol. J. – start-page: 724 year: April 2018 end-page: 729 – volume: 8 start-page: 109 issue: 1 year: 2015 end-page: 116 article-title: An improved CPE localization algorithm for wireless sensor networks publication-title: Int. J. Future Gen. Commun. Netw. – start-page: 6 year: July 2017 end-page: 10 – volume: 20 start-page: 250 issue: 1 year: 2019 end-page: 260 article-title: MEMS based IMU drift minimization: Sage Husa adaptive robust Kalman filtering publication-title: IEEE Sens. J. – start-page: 3710 year: May 2008 end-page: 3716 – volume: 72 start-page: 808 year: 2018 end-page: 827 article-title: Improved range‐free localization for three‐dimensional wireless sensor networks using genetic algorithm publication-title: Comput. Electr. Eng. – year: 2006 – start-page: 558 year: October 2019 end-page: 571 – volume: 19 start-page: 1371 issue: 6 year: 2019 article-title: Adaptive unscented Kalman filter for target tracking with unknown time‐varying noise covariance publication-title: Sensors – volume: 18 start-page: 4335 issue: 12 year: 2018 article-title: Hybrid adaptive cubature Kalman filter with unknown variance of measurement noise publication-title: Sensors – volume: 29 start-page: 201 issue: 2 year: 2015 end-page: 223 article-title: Windowing and random weighting‐based adaptive unscented Kalman filter publication-title: Int. J. Adapt. Control Signal Process. – start-page: 12171 year: October 2019 – ident: e_1_2_8_9_1 doi: 10.1016/j.comcom.2006.12.020 – ident: e_1_2_8_18_1 doi: 10.1109/TAES.2017.2756763 – start-page: 6 volume-title: Proc. IEEE 2nd Int. Conf. on Opto‐Electronic Information Processing year: 2017 ident: e_1_2_8_25_1 – ident: e_1_2_8_39_1 doi: 10.1109/CCSSE.2014.7224505 – ident: e_1_2_8_46_1 doi: 10.1007/s12083-015-0372-9 – ident: e_1_2_8_14_1 doi: 10.1002/0470045345 – ident: e_1_2_8_51_1 doi: 10.1109/ROBOT.2008.4543780 – ident: e_1_2_8_4_1 doi: 10.1016/j.adhoc.2017.11.008 – volume: 34 start-page: 2950 issue: 15 year: 2016 ident: e_1_2_8_47_1 article-title: Distance estimation based on RSSI and log‐normal shadowing models for ZigBee wireless sensor network publication-title: Eng. Technol. J. doi: 10.30684/etj.34.15A.15 – ident: e_1_2_8_27_1 doi: 10.1109/ICMA.2017.8016075 – ident: e_1_2_8_10_1 doi: 10.1109/JSEN.2015.2510020 – ident: e_1_2_8_22_1 doi: 10.1109/C-CODE.2017.7918918 – ident: e_1_2_8_7_1 doi: 10.3390/s18020332 – ident: e_1_2_8_49_1 doi: 10.1109/TSP.2007.906770 – ident: e_1_2_8_42_1 doi: 10.1109/JSEN.2019.2941273 – ident: e_1_2_8_30_1 doi: 10.1109/INFCOMW.2018.8406856 – ident: e_1_2_8_45_1 doi: 10.1049/iet-rsn.2014.0533 – ident: e_1_2_8_23_1 doi: 10.1016/j.compeleceng.2017.12.036 – ident: e_1_2_8_29_1 doi: 10.1109/LCOMM.2017.2765642 – ident: e_1_2_8_12_1 doi: 10.1109/KCIC.2016.7883626 – ident: e_1_2_8_11_1 doi: 10.1109/WiSPNET.2016.7566539 – start-page: 391 volume-title: Proc. Int. Conf. on Communication, Computer and Power year: 2009 ident: e_1_2_8_53_1 – ident: e_1_2_8_41_1 doi: 10.3390/s18124335 – ident: e_1_2_8_24_1 doi: 10.1007/978-981-10-6544-6_12 – volume: 153 start-page: 13 issue: 6 year: 2013 ident: e_1_2_8_33_1 article-title: Research on target tracking based on unscented Kalman filter publication-title: Sens. Transducers – ident: e_1_2_8_35_1 doi: 10.3390/app9091916 – ident: e_1_2_8_43_1 doi: 10.1109/WiMob.2009.30 – start-page: 558 volume-title: Proc. Conf. on Chinese Intelligent Systems Conf. year: 2019 ident: e_1_2_8_48_1 – ident: e_1_2_8_34_1 doi: 10.3390/s16060805 – ident: e_1_2_8_16_1 doi: 10.1109/TAC.2017.2730480 – ident: e_1_2_8_38_1 doi: 10.1002/acs.2467 – volume: 8 start-page: 109 issue: 1 year: 2015 ident: e_1_2_8_26_1 article-title: An improved CPE localization algorithm for wireless sensor networks publication-title: Int. J. Future Gen. Commun. Netw. – ident: e_1_2_8_13_1 doi: 10.1109/JSEN.2018.2873357 – ident: e_1_2_8_50_1 doi: 10.1109/LWC.2017.2762305 – ident: e_1_2_8_28_1 doi: 10.1109/DISCOVER.2016.7806221 – ident: e_1_2_8_8_1 doi: 10.1109/TIT.2017.2693180 – ident: e_1_2_8_19_1 doi: 10.3390/s19061371 – ident: e_1_2_8_20_1 doi: 10.1109/TII.2019.2909135 – ident: e_1_2_8_36_1 doi: 10.1016/j.asr.2014.12.005 – ident: e_1_2_8_15_1 doi: 10.1016/j.actaastro.2015.12.014 – ident: e_1_2_8_31_1 doi: 10.1109/JSEN.2019.2892652 – volume-title: Hybrid cubature filter: theory and tracking application year: 2009 ident: e_1_2_8_52_1 – ident: e_1_2_8_37_1 doi: 10.1016/j.egypro.2018.09.204 – ident: e_1_2_8_2_1 doi: 10.1109/ICACDOT.2016.7877655 – ident: e_1_2_8_40_1 doi: 10.1109/ICMA.2017.8016115 – ident: e_1_2_8_32_1 doi: 10.1109/ICCAS.2015.7364990 – ident: e_1_2_8_5_1 doi: 10.1109/INDIN.2017.8104800 – ident: e_1_2_8_44_1 doi: 10.1016/j.comcom.2016.10.011 – ident: e_1_2_8_6_1 doi: 10.14257/ijsh.2015.9.5.19 – ident: e_1_2_8_21_1 doi: 10.1088/1742-6596/1325/1/012171 – start-page: 479 volume-title: Proc. Int. Conf. on Cognitive Systems and Signal Processing year: 2016 ident: e_1_2_8_3_1 – start-page: 1 volume-title: Proc. IEEE Int. Conf. on Information Fusion year: 2011 ident: e_1_2_8_54_1 – ident: e_1_2_8_17_1 doi: 10.1109/LSP.2017.2724848 |
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| Snippet | Current target tracking algorithms for wireless sensor networks in noise environments have large positioning errors. Owing to the environmental noise, Kalman... |
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| SubjectTerms | adaptive Kalman filters adaptive KF current target tracking algorithms environmental noise existing target tracking algorithm higher estimation accuracy Kalman filters moving target noise environments noise perception noise‐aware algorithm noise‐aware manoeuvring target tracking algorithm noise‐aware target tracking algorithm novel adaptive cubature Kalman filter numerical analysis positioning errors Research Article second‐order estimation accuracy target position target tracking third‐order adaptive cubature KF third‐order noise statistic estimator time‐varying tracking filters wireless sensor networks |
| Title | Noise-aware manoeuvring target tracking algorithm in wireless sensor networks by a novel adaptive cubature Kalman filter |
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