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August & September  2019, 12(4&5): 1251-1264. doi: 10.3934/dcdss.2019086

Automatic tracking and positioning algorithm for moving targets in complex environment

1. 

Unmanned Aerial Vehicle Research Institute, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

2. 

Department of Mathematics UMBA, University of Mostaganem Algeria, Algeria

* Corresponding author: Rong Liu

Received  June 2017 Revised  November 2017 Published  November 2018

Nowadays, when moving targets are located in complex environment, the positioning algorithm takes longer time, and the result is not consistent with the actual positioning of the moving target, which has the problem of low positioning efficiency and inaccurate positioning results. In this paper, a moving target automatic tracking and positioning algorithm is proposed in the complex environment, which establishes the geodetic coordinate system and the space rectangular coordinate system, and completes the transformation between the geodetic coordinate system and the rectangular coordinate system, so as to improve the accuracy of the positioning result. The signal is rebuilt and the MIMO radar positioning model is used to complete the automatic tracking and positioning of the moving target in complex environment, to reduce the time consuming. The experimental results show that the proposed method can quickly and accurately track and locate the moving target in complex environment.

Citation: Rong Liu, Saini Jonathan Tishari. Automatic tracking and positioning algorithm for moving targets in complex environment. Discrete & Continuous Dynamical Systems - S, 2019, 12 (4&5) : 1251-1264. doi: 10.3934/dcdss.2019086
References:
[1]

A. H. Abdullah and et al., Mathematics teachers' level of knowledge and practice on the implementation of higher-order thinking skills (hots), Eurasia Journal of Mathematics Science & Technology Education, 13 (2016), 3-17. Google Scholar

[2]

A. Ahadi and A. Dehghan, The inapproximability for the (0, 1)-additive number, Discrete Mathematics and Theoretical Computer Science, 17 (2016), 217-226.   Google Scholar

[3]

F. Altinay-Gazi Zehra—Altinay-Aksal, Technology as mediation tool for improving teaching profession in higher education practices, Eurasia Journal of Mathematics Science & Technology Education, 13 (2017), 803-813. Google Scholar

[4]

M. M. A. M. Aly and M. A. H. El-Sayed, Enhanced fault location algorithm for smart grid containing wind farm using wireless communication facilities, Iet Generation Transmission & Distribution, 10 (2016), 2231-2239.   Google Scholar

[5]

L. B. and L. W. S., Indoor positioning method based on cosine similarity of fingerprint matching algorithm, Bulletin of Science and Technology, 3 (2017), 198-202. Google Scholar

[6]

T. P. S. Bains and M. R. D. Zadeh, Supplementary impedance-based fault-location algorithm for series-compensated lines, IEEE Transactions on Power Delivery, 31 (2016), 334-342.   Google Scholar

[7]

A. Basar and M. Y. Abbasi, On ordered bi-ideals in ordered-semigroups, Journal of Discrete Mathematical Sciences and Cryptography, 20 (2017), 645-652.  doi: 10.1080/09720529.2015.1130474.  Google Scholar

[8]

T. BroughL. CiobanuM. Elder and G. Zetzsche, Permutations of context-free, et0l and indexed languages, Discrete Mathematics & Theoretical Computer Science, 17 (2016), 167-178.   Google Scholar

[9]

J. ByrkaS. Li and B. Rybicki, Improved Approximation Algorithm for k-level Uncapacitated Facility Location Problem (with Penalties), Theory Comput. Syst., 58 (2016), 19-44.  doi: 10.1007/s00224-014-9575-3.  Google Scholar

[10]

Y. Cao, Optimal investment-reinsurance problem for an insurer with jump-diffusion risk process: correlated of brownian motions, Journal of Interdisciplinary Mathematics, 20 (2017), 497-511.   Google Scholar

[11]

M. Chen and C. X. Xu, Analysis of optimal utilization model of coastline resources in jiangsu province, Journal of Interdisciplinary Mathematics, 20 (2017), 1441-1444.   Google Scholar

[12]

P. S. Davis and T. L. Ray, A branch ound algorithm for the capacitated facilities location problem, Naval Research Logistics, 16 (2015), 331-344. Google Scholar

[13]

W. Gao and W. Wang, A tight neighborhood union condition on fractional (g, f, n', m)-critical deleted graphs, Colloquium Mathematicum, 149 (2017), 291-298.  doi: 10.4064/cm6959-8-2016.  Google Scholar

[14]

W. GaoL. ZhuY. Guo and K. Wang, Ontology learning algorithm for similarity measuring and ontology mapping using linear programming, Journal of Intelligent & Fuzzy Systems, 33 (2017), 3153-3163.   Google Scholar

[15]

Y. Gao, Optimization design of fast query system for retrieval information from large amount of books, Modern Electronics Technique, 9 (2016), 422-425.   Google Scholar

[16]

M. Ghorbani, An evolutionary algorithm for a new multi-objective location-inventory model in a distribution network with transportation modes and third-party logistics providers, International Journal of Production Research, 53 (2015), 1038-1050.   Google Scholar

[17]

R. J. Hamidi and H. Livani, Traveling-wave-based fault-location algorithm for hybrid multiterminal circuits, IEEE Transactions on Power Delivery, 32 (2017), 135-144.   Google Scholar

[18]

B. Hartke, Global cluster geometry optimization by a phenotype algorithm with niches: Location of elusive minima, and low rder scaling with cluster size, Journal of Computational Chemistry, 20 (2015), 1752-1759.   Google Scholar

[19]

T. JinY. F. Niu and L. Zhou, Methods of evaluating cognitive performance of products digital interface, Journal of Discrete Mathematical Sciences & Cryptography, 20 (2017), 295-308.   Google Scholar

[20]

Z. LiuM. ChaoJ. ZhangX. ZhangY. Liu and J. Zhang, Research on mathematical properties of localization algorithm based on sensor relative position in wsn, Journal of Jilin University(Information Science Edition, 6 (2015), 685-689.   Google Scholar

[21]

G. PrestonZ. M. RadojevicC. H. Kim and V. Terzija, New settings-free fault location algorithm based on synchronised sampling, Iet Generation Transmission & Distribution, 5 (2015), 376-83.   Google Scholar

[22]

S. SunK. DongJ. J. Xiu and Y. Liu, A passive source localization algorithm with multiple moving observers using tdoa/groa measurements based on cwls, Journal of China Academy of Electronics & Information Technology, 5 (2016), 540-546.   Google Scholar

[23]

Y. SunJ. QiR. ZhangY. Chen and X. Du, Mapreduce based location selection algorithm for utility maximization with capacity constraints, Computing, 97 (2015), 403-423.  doi: 10.1007/s00607-013-0382-5.  Google Scholar

[24]

P. H. Tseng and K. T. Lee, A femto-aided location tracking algorithm in lte-a heterogeneous networks, IEEE Transactions on Vehicular Technology, 66 (2017), 748-762.   Google Scholar

[25]

G. Weckman, Applying genetic algorithm to a new location and routing model of hazardous materials, International Journal of Production Research, 53 (2015), 916-928.   Google Scholar

[26]

W. Yi, Assessment study on brain wave predictive ability to policemen's safety law enforcement, Journal of Discrete Mathematical Sciences and Cryptography, 20 (2017), 193-204.   Google Scholar

[27]

J. J. Zhang and K. Qiang, Modeling of complex information system based on hierarchical decision-making theory, Journal of Discrete Mathematical Sciences & Cryptography, 20 (2017), 137-148.   Google Scholar

show all references

References:
[1]

A. H. Abdullah and et al., Mathematics teachers' level of knowledge and practice on the implementation of higher-order thinking skills (hots), Eurasia Journal of Mathematics Science & Technology Education, 13 (2016), 3-17. Google Scholar

[2]

A. Ahadi and A. Dehghan, The inapproximability for the (0, 1)-additive number, Discrete Mathematics and Theoretical Computer Science, 17 (2016), 217-226.   Google Scholar

[3]

F. Altinay-Gazi Zehra—Altinay-Aksal, Technology as mediation tool for improving teaching profession in higher education practices, Eurasia Journal of Mathematics Science & Technology Education, 13 (2017), 803-813. Google Scholar

[4]

M. M. A. M. Aly and M. A. H. El-Sayed, Enhanced fault location algorithm for smart grid containing wind farm using wireless communication facilities, Iet Generation Transmission & Distribution, 10 (2016), 2231-2239.   Google Scholar

[5]

L. B. and L. W. S., Indoor positioning method based on cosine similarity of fingerprint matching algorithm, Bulletin of Science and Technology, 3 (2017), 198-202. Google Scholar

[6]

T. P. S. Bains and M. R. D. Zadeh, Supplementary impedance-based fault-location algorithm for series-compensated lines, IEEE Transactions on Power Delivery, 31 (2016), 334-342.   Google Scholar

[7]

A. Basar and M. Y. Abbasi, On ordered bi-ideals in ordered-semigroups, Journal of Discrete Mathematical Sciences and Cryptography, 20 (2017), 645-652.  doi: 10.1080/09720529.2015.1130474.  Google Scholar

[8]

T. BroughL. CiobanuM. Elder and G. Zetzsche, Permutations of context-free, et0l and indexed languages, Discrete Mathematics & Theoretical Computer Science, 17 (2016), 167-178.   Google Scholar

[9]

J. ByrkaS. Li and B. Rybicki, Improved Approximation Algorithm for k-level Uncapacitated Facility Location Problem (with Penalties), Theory Comput. Syst., 58 (2016), 19-44.  doi: 10.1007/s00224-014-9575-3.  Google Scholar

[10]

Y. Cao, Optimal investment-reinsurance problem for an insurer with jump-diffusion risk process: correlated of brownian motions, Journal of Interdisciplinary Mathematics, 20 (2017), 497-511.   Google Scholar

[11]

M. Chen and C. X. Xu, Analysis of optimal utilization model of coastline resources in jiangsu province, Journal of Interdisciplinary Mathematics, 20 (2017), 1441-1444.   Google Scholar

[12]

P. S. Davis and T. L. Ray, A branch ound algorithm for the capacitated facilities location problem, Naval Research Logistics, 16 (2015), 331-344. Google Scholar

[13]

W. Gao and W. Wang, A tight neighborhood union condition on fractional (g, f, n', m)-critical deleted graphs, Colloquium Mathematicum, 149 (2017), 291-298.  doi: 10.4064/cm6959-8-2016.  Google Scholar

[14]

W. GaoL. ZhuY. Guo and K. Wang, Ontology learning algorithm for similarity measuring and ontology mapping using linear programming, Journal of Intelligent & Fuzzy Systems, 33 (2017), 3153-3163.   Google Scholar

[15]

Y. Gao, Optimization design of fast query system for retrieval information from large amount of books, Modern Electronics Technique, 9 (2016), 422-425.   Google Scholar

[16]

M. Ghorbani, An evolutionary algorithm for a new multi-objective location-inventory model in a distribution network with transportation modes and third-party logistics providers, International Journal of Production Research, 53 (2015), 1038-1050.   Google Scholar

[17]

R. J. Hamidi and H. Livani, Traveling-wave-based fault-location algorithm for hybrid multiterminal circuits, IEEE Transactions on Power Delivery, 32 (2017), 135-144.   Google Scholar

[18]

B. Hartke, Global cluster geometry optimization by a phenotype algorithm with niches: Location of elusive minima, and low rder scaling with cluster size, Journal of Computational Chemistry, 20 (2015), 1752-1759.   Google Scholar

[19]

T. JinY. F. Niu and L. Zhou, Methods of evaluating cognitive performance of products digital interface, Journal of Discrete Mathematical Sciences & Cryptography, 20 (2017), 295-308.   Google Scholar

[20]

Z. LiuM. ChaoJ. ZhangX. ZhangY. Liu and J. Zhang, Research on mathematical properties of localization algorithm based on sensor relative position in wsn, Journal of Jilin University(Information Science Edition, 6 (2015), 685-689.   Google Scholar

[21]

G. PrestonZ. M. RadojevicC. H. Kim and V. Terzija, New settings-free fault location algorithm based on synchronised sampling, Iet Generation Transmission & Distribution, 5 (2015), 376-83.   Google Scholar

[22]

S. SunK. DongJ. J. Xiu and Y. Liu, A passive source localization algorithm with multiple moving observers using tdoa/groa measurements based on cwls, Journal of China Academy of Electronics & Information Technology, 5 (2016), 540-546.   Google Scholar

[23]

Y. SunJ. QiR. ZhangY. Chen and X. Du, Mapreduce based location selection algorithm for utility maximization with capacity constraints, Computing, 97 (2015), 403-423.  doi: 10.1007/s00607-013-0382-5.  Google Scholar

[24]

P. H. Tseng and K. T. Lee, A femto-aided location tracking algorithm in lte-a heterogeneous networks, IEEE Transactions on Vehicular Technology, 66 (2017), 748-762.   Google Scholar

[25]

G. Weckman, Applying genetic algorithm to a new location and routing model of hazardous materials, International Journal of Production Research, 53 (2015), 916-928.   Google Scholar

[26]

W. Yi, Assessment study on brain wave predictive ability to policemen's safety law enforcement, Journal of Discrete Mathematical Sciences and Cryptography, 20 (2017), 193-204.   Google Scholar

[27]

J. J. Zhang and K. Qiang, Modeling of complex information system based on hierarchical decision-making theory, Journal of Discrete Mathematical Sciences & Cryptography, 20 (2017), 137-148.   Google Scholar

Figure 1.  Model of pin hole imaging
Figure 2.  Diagram of corner system $\varphi, \omega$ and $\kappa $
Figure 3.  MIMO radar model
Figure 4.  Comparison of the calculated position and the actual position of a ship
Figure 5.  Comparison of calculate longitude and actual longitude of ship
Figure 6.  Comparison of the calculated latitudes and the actual latitudes of the ship
Figure 7.  the time used for positioning by the three different methods
Table 1.  test data table of the target location algorithm
TargetShip 1Ship 2Ship 3Ship 4
Algorithm parameters$\Phi (^{\circ})$32393129
$\omega (^{\circ})$-1-1-1-1
$\kappa (^{\circ})$0.20.20.20.2
x(mm)14-16-1-23
y(mm)92-9-7
f(mm)148.51155148.51133
X$_{C}$(m)-2734008.694-2733672.0788-2734008.694-2733672.0788
Y$_{C}$(m)5120687.46805121154.10445120687.46805121154.1044
Z$_{C}$(m)2634082.84852633528.70102634082.84852633528.7010
Calculated coordinate118$^{\circ}$05.872'E,118$^{\circ}$05.572'E,118$^{\circ}$05.883'E,118$^{\circ}$05.586'E,
24$^{\circ}$33.109'N24$^{\circ}$32.779'N24$^{\circ}$33.112'N24$^{\circ}$32.773'N
Actual coordinate118$^{\circ}$05.906'E,118$^{\circ}$05.493'E,118$^{\circ}$05.896'E,118$^{\circ}$05.464'E,
24$^{\circ}$33.055'N24$^{\circ}$32.700'N24$^{\circ}$33.050'N24$^{\circ}$32.655'N
ErrorLongitude/'0.0340.0790.0130.122
Latitude/'0.0540.0790.0620.118
TargetShip 1Ship 2Ship 3Ship 4
Algorithm parameters$\Phi (^{\circ})$32393129
$\omega (^{\circ})$-1-1-1-1
$\kappa (^{\circ})$0.20.20.20.2
x(mm)14-16-1-23
y(mm)92-9-7
f(mm)148.51155148.51133
X$_{C}$(m)-2734008.694-2733672.0788-2734008.694-2733672.0788
Y$_{C}$(m)5120687.46805121154.10445120687.46805121154.1044
Z$_{C}$(m)2634082.84852633528.70102634082.84852633528.7010
Calculated coordinate118$^{\circ}$05.872'E,118$^{\circ}$05.572'E,118$^{\circ}$05.883'E,118$^{\circ}$05.586'E,
24$^{\circ}$33.109'N24$^{\circ}$32.779'N24$^{\circ}$33.112'N24$^{\circ}$32.773'N
Actual coordinate118$^{\circ}$05.906'E,118$^{\circ}$05.493'E,118$^{\circ}$05.896'E,118$^{\circ}$05.464'E,
24$^{\circ}$33.055'N24$^{\circ}$32.700'N24$^{\circ}$33.050'N24$^{\circ}$32.655'N
ErrorLongitude/'0.0340.0790.0130.122
Latitude/'0.0540.0790.0620.118
Table 2.  test data table of the target location algorithm
TargetShip 5Ship 6Ship 7Ship 8
Algorithm parameters$\Phi (^{\circ})$21242525
$\omega (^{\circ})$$-$1$-$1$-$1$-$1
$\kappa (^{\circ})$0.20.20.20.2
x(mm)$-$7$-$9$-$11$-$2
y(mm)$-$12$-$11$-$5$-$5
f(mm)166155155126.6
X$_{C}$(m)$-$2733672.0788$-$2733672.0788$-$2733672.0788$-$2733672.0788
Y$_{C}$(m)5121154.10445121154.10445121154.10445121154.1044
Z$_{C}$(m)2633528.70102633528.70102633528.70102633528.7010
Calculated coordinate118$^{\circ}$05.587'E,118$^{\circ}$05.586'E,118$^{\circ}$05.583'E,118$^{\circ}$05.580'E,
24$^{\circ}$32.774'N24$^{\circ}$32.775'N24$^{\circ}$32.773'N24$^{\circ}$32.776'N
Actual coordinate118$^{\circ}$05.594'E,118$^{\circ}$05.480'E,118$^{\circ}$05.427'E,118$^{\circ}$05.459'E,
24$^{\circ}$32.798'N24$^{\circ}$32.676'N24$^{\circ}$32.669'N24$^{\circ}$32.690'N
ErrorLongitude/'0.0070.1060.1560.121
Latitude/'0.0240.0990.1040.086
TargetShip 5Ship 6Ship 7Ship 8
Algorithm parameters$\Phi (^{\circ})$21242525
$\omega (^{\circ})$$-$1$-$1$-$1$-$1
$\kappa (^{\circ})$0.20.20.20.2
x(mm)$-$7$-$9$-$11$-$2
y(mm)$-$12$-$11$-$5$-$5
f(mm)166155155126.6
X$_{C}$(m)$-$2733672.0788$-$2733672.0788$-$2733672.0788$-$2733672.0788
Y$_{C}$(m)5121154.10445121154.10445121154.10445121154.1044
Z$_{C}$(m)2633528.70102633528.70102633528.70102633528.7010
Calculated coordinate118$^{\circ}$05.587'E,118$^{\circ}$05.586'E,118$^{\circ}$05.583'E,118$^{\circ}$05.580'E,
24$^{\circ}$32.774'N24$^{\circ}$32.775'N24$^{\circ}$32.773'N24$^{\circ}$32.776'N
Actual coordinate118$^{\circ}$05.594'E,118$^{\circ}$05.480'E,118$^{\circ}$05.427'E,118$^{\circ}$05.459'E,
24$^{\circ}$32.798'N24$^{\circ}$32.676'N24$^{\circ}$32.669'N24$^{\circ}$32.690'N
ErrorLongitude/'0.0070.1060.1560.121
Latitude/'0.0240.0990.1040.086
[1]

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