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Smart City Moving Target Tracking Algorithm Based on Quantum Genetic and Particle Filter
المؤلفون المشاركون
Liu, Zhigang
Shang, Jin
Hua, Xufen
المصدر
Wireless Communications and Mobile Computing
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-9، 9ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-06-20
دولة النشر
مصر
عدد الصفحات
9
التخصصات الرئيسية
تكنولوجيا المعلومات وعلم الحاسوب
الملخص EN
In the application of moving target tracking in smart city, particle filter technology has the advantages of dealing with nonlinear and non-Gaussian problems, but when the standard particle filter uses resampling method to solve the degradation phenomenon, simply copying the particles will cause local optimization difficulties, resulting in unstable filtering accuracy.
In this paper, a particle filter algorithm combined with quantum genetic algorithm (QGA) is proposed to solve the above problems.
Aiming at the problem of particle exhaustion in particle filter, the algorithm adopts the method of combining evolutionary algorithm.
Each particle in particle filter is regarded as a chromosome in genetic algorithm, and the fitness of each chromosome corresponds to the weight of particle.
For each particle state with weight, the particle is first binary coded with qubit and quantum superposition state, and then quantum rotation gate is used for selection, crossing, mutation, and other operations, after a set number of iterations, the final particle set with accuracy and better diversity.
In this paper, the filter state estimation and RMSF of N=50 and N=100 for nonlinear target tracking and the comparison of real state and state estimation trajectory in time-constant model under nonlinear target tracking are given.
It can be seen that in nonlinear state, the quantum genetic and particle filter (QGPF) algorithm can achieve a higher accuracy of state estimation, and the filtering error of QGPF algorithm at each time is relatively uniform, which shows that the algorithm in this paper has better algorithm stability.
Under the time-constant model, the algorithm fits the real state and realizes stable and accurate tracking.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Liu, Zhigang& Shang, Jin& Hua, Xufen. 2020. Smart City Moving Target Tracking Algorithm Based on Quantum Genetic and Particle Filter. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1214795
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Liu, Zhigang…[et al.]. Smart City Moving Target Tracking Algorithm Based on Quantum Genetic and Particle Filter. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1214795
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Liu, Zhigang& Shang, Jin& Hua, Xufen. Smart City Moving Target Tracking Algorithm Based on Quantum Genetic and Particle Filter. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1214795
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1214795
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
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