{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,16]],"date-time":"2026-03-16T17:46:13Z","timestamp":1773683173037,"version":"3.50.1"},"reference-count":38,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2016,3,14]],"date-time":"2016-03-14T00:00:00Z","timestamp":1457913600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,3,14]]},"abstract":"\n Purpose<\/jats:title>\n \u2013 With increasing demand of localization service in challenging environments where Global Navigation Satellite Systems (GNSS) signals are considerably weak, a powerful approach, the collective detection (CD), has been developed. However, traditional CD techniques are computationally intense due to the large clock bias search space. Therefore, the purpose of this paper is to develop a new scheme of CD with less computational burden, in order to accelerate the detection and location process. <\/jats:p>\n <\/jats:sec>\n \n Design\/methodology\/approach<\/jats:title>\n \u2013 This paper proposes a new scheme of CD. It reformulates the problem of GNSS signal detection as an optimization problem, and solves it with the aid of an improved Pigeon-Inspired Optimization (PIO). With the improved PIO algorithm adopted, the positioning algorithm arrives to evaluate only a part of the points in the search space, avoiding the problems of grid-search method which is universally adopted. <\/jats:p>\n <\/jats:sec>\n \n Findings<\/jats:title>\n \u2013 Faced with the complex optimization problem, the improved PIO algorithm proves to have good performance. In the acquisition of simulated and real signals, the proposed scheme of CD with the improved PIO algorithm also have better efficiency, precision and stability than traditional CD algorithm. Besides, the improved PIO algorithm also proves to be a better candidate to be integrated into the proposed scheme than particle swarm optimization, differential evolution and PIO. <\/jats:p>\n <\/jats:sec>\n \n Originality\/value<\/jats:title>\n \u2013 The novelty associated with this paper is the proposition of the new scheme of CD and the improvement of PIO algorithm. Thus, this paper introduces another possibility to ameliorate the traditional CD.<\/jats:p>\n <\/jats:sec>","DOI":"10.1108\/ijicc-08-2015-0028","type":"journal-article","created":{"date-parts":[[2016,3,9]],"date-time":"2016-03-09T10:33:21Z","timestamp":1457519601000},"page":"105-123","source":"Crossref","is-referenced-by-count":10,"title":["A type of collective detection scheme with improved pigeon-inspired optimization"],"prefix":"10.1108","volume":"9","author":[{"given":"Zhengxuan","family":"JIA","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","reference":[{"key":"key2020121721083251600_b1","doi-asserted-by":"crossref","unstructured":"Ababneh, J.\n (2015), \u201cGreedy particle swarm and biogeography-based optimization algorithm\u201d, \n International Journal of Intelligent Computing and Cybernetics\n , Vol. 8 No. 1, pp. 28-49.","DOI":"10.1108\/IJICC-01-2014-0003"},{"key":"key2020121721083251600_b2","doi-asserted-by":"crossref","unstructured":"Axelrad, P.\n , \n Bradley, B.K.\n , \n Donna, J.\n , \n Mitchell, M.\n and \n Mohiuddin, S.\n (2011), \u201cCollective detection and direct positioning using multiple GNSS satellites\u201d, \n Navigation\n , Vol. 58 No. 4, pp. 305-321.","DOI":"10.1002\/j.2161-4296.2011.tb02588.x"},{"key":"key2020121721083251600_b4","unstructured":"Borre, K.\n , \n Akos, D.M.\n , \n Bertelsen, N.\n , \n Rinder, P.\n and \n Jensen, S.H.\n (2007), \n A Software-Defined GPS and Galileo Receiver: A Single-Frequency Approach\n , Springer Science \n\t\t\t\t\t&\n\t\t\t\t Business Media, Boston, MA, Basel and Berlin."},{"key":"key2020121721083251600_b6","unstructured":"Cheong, J.W.\n (2011), \u201cTowards multi-constellation collective detection for weak signals: a comparative experimental analysis\u201d, Proceedings of the ION GNSS, pp. 3709-3719."},{"key":"key2020121721083251600_b7","unstructured":"Cheong, J.W.\n , \n Dempster, A.G.\n and \n Rizos, C.\n (2011a), \u201cHybrid of collective detection with conventional detection for weak signal acquisition\u201d, Proceedings of the International GNSS Society Symposium (IGNSS 2011), University of New South Wales, Sydney, NSW, November 15-17."},{"key":"key2020121721083251600_b8","unstructured":"Cheong, J.W.\n , \n Wu, J.\n , \n Dempster, A.G.\n and \n Rizos, C.\n (2011b), \u201cEfficient implementation of collective detection\u201d, IGNSS Symposium, pp. 15-17."},{"key":"key2020121721083251600_b10","doi-asserted-by":"crossref","unstructured":"Closas, P.\n , \n Fern\u00e1ndez-Prades, C.\n and \n Fern\u00e1ndez-Rubio, J.A.\n (2007), \u201cMaximum likelihood estimation of position in GNSS\u201d, \n Signal Processing Letters, IEEE\n , Vol. 14 No. 5, pp. 359-362.","DOI":"10.1109\/LSP.2006.888360"},{"key":"key2020121721083251600_b11","unstructured":"Dedes, G.\n and \n Dempster, A.G.\n (2005), \u201cIndoor GPS positioning\u201d, Proceedings of the IEEE Semiannual Vehicular Technology Conference, Intercontinental Hotels Dallas, Dallas, TX, September 25-28."},{"key":"key2020121721083251600_b12","doi-asserted-by":"crossref","unstructured":"Duan, H.\n and \n Deng, Y.M.\n (2014), \u201cBiologically inspired model with feature selection for tar-get recognition using biogeography-based optimization\u201d, \n AIAA Journal of Aerospace Information Systems\n , Vol. 11 No. 7, pp. 433-446.","DOI":"10.2514\/1.I010122"},{"key":"key2020121721083251600_b14","doi-asserted-by":"crossref","unstructured":"Duan, H.\n and \n Qiao, P.\n (2014), \u201cPigeon-inspired optimization: a new swarm intelligence optimizer for air robot path planning\u201d, \n International Journal of Intelligent Computing and Cybernetics\n , Vol. 7 No. 1, pp. 24-37.","DOI":"10.1108\/IJICC-02-2014-0005"},{"key":"key2020121721083251600_b13","doi-asserted-by":"crossref","unstructured":"Duan, H.\n , \n Luo, Q.\n , \n Shi, Y.\n and \n Ma, G.\n (2013), \u201cHybrid particle swarm optimization and genetic algorithm for multi-UAV formation reconfiguration\u201d, \n Computational Intelligence Magazine, IEEE\n , Vol. 8 No. 3, pp. 16-27.","DOI":"10.1109\/MCI.2013.2264577"},{"key":"key2020121721083251600_b17","unstructured":"Esteves, P.\n (2014a), \u201cTechniques d\u2019acquisition \u00e0 haute sensibilit\u00e9 des signaux GNSS\u201d, PhD thesis, ISAE, Toulouse."},{"key":"key2020121721083251600_b16","unstructured":"Esteves, P.\n , \n Sahmoudi, M.\n and \n Ries, L.\n (2014b), \u201cCollective detection of multi-GNSS signals: vector-acquisition promises sensitivity and reliability improvement\u201d, Inside GNSS Magazine, May\/June, pp. 54-65."},{"key":"key2020121721083251600_b18","doi-asserted-by":"crossref","unstructured":"Geis, M.\n and \n Middendorf, M.\n (2008), \u201cCreating melodies and baroque harmonies with ant colony optimization\u201d, \n International Journal of Intelligent Computing and Cybernetics\n , Vol. 1 No. 2, pp. 213-238.","DOI":"10.1108\/17563780810874726"},{"key":"key2020121721083251600_b19","doi-asserted-by":"crossref","unstructured":"Grewal, M.S.\n , \n Weill, L.R.\n and \n Andrews, A.P.\n (2007), \n Global Positioning Systems, Inertial Navigation, and Integration\n , John Wiley \n\t\t\t\t\t&\n\t\t\t\t Sons, New York, NY.","DOI":"10.1002\/0470099720"},{"key":"key2020121721083251600_b21","doi-asserted-by":"crossref","unstructured":"Kennedy, J.\n and \n Eberhart, R.\n (1995), \u201cParticle swarm optimization\u201d, Proceedings, IEEE International Conference on Neural Networks, Vol. 4, pp. 1942-1948.","DOI":"10.1109\/ICNN.1995.488968"},{"key":"key2020121721083251600_b22","unstructured":"Kennedy, J.\n , \n Eberhart, R.C.\n and \n Shi, Y.H.\n (2001), \n Swarm Intelligence\n , Morgan Kauffmann, San Mateo, CA."},{"key":"key2020121721083251600_b24","doi-asserted-by":"crossref","unstructured":"Li, C.\n and \n Duan, H.\n (2014a), \u201cTarget detection approach for UAVs via improved pigeon-inspired optimization and edge potential function\u201d, \n Aerospace Science and Technology\n , Vol. 39 No. 1, pp. 352-360.","DOI":"10.1016\/j.ast.2014.10.007"},{"key":"key2020121721083251600_b25","doi-asserted-by":"crossref","unstructured":"Li, H.\n and \n Duan, H.\n (2014b), \u201cBloch quantum-behaved Pigeon-inspired optimization for continuous optimization problems\u201d, Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE, pp. 2634-2638 (in Chinese).","DOI":"10.1109\/CGNCC.2014.7007584"},{"key":"key2020121721083251600_b23","doi-asserted-by":"crossref","unstructured":"Li, L.\n , \n Cheong, J.W.\n , \n Wu, J.\n and \n Dempster, A.G.\n (2014), \u201cImprovement to multi-resolution collective detection in GNSS receivers\u201d, \n Journal of Navigation\n , Vol. 67 No. 2, pp. 277-293.","DOI":"10.1017\/S0373463313000635"},{"key":"key2020121721083251600_b26","doi-asserted-by":"crossref","unstructured":"Luo, Q.\n and \n Duan, H.\n (2014), \u201cChaotic artificial bee colony approach to step planning of maintaining balance for quadruped robot\u201d, \n International Journal of Intelligent Computing and Cybernetics\n , Vol. 7 No. 2, pp. 175-191.","DOI":"10.1108\/IJICC-05-2013-0028"},{"key":"key2020121721083251600_b27","doi-asserted-by":"crossref","unstructured":"Narula, L.\n , \n Singh, K.P.\n and \n Petovello, M.G.\n (2014), \u201cAccelerated collective detection technique for weak GNSS signal environment\u201d, Ubiquitous Positioning Indoor Navigation and Location Based Service (UPINLBS), IEEE, pp. 81-89.","DOI":"10.1109\/UPINLBS.2014.7033713"},{"key":"key2020121721083251600_b28","unstructured":"Omar, A.B.\n , \n Sahmoudi, M.\n , \n Esteves, P.\n , \n Ries, L.\n , \n Andrianarison, M.\n and \n Landry, R.\n (2014), \u201cA new method of collective acquisition of multiple GNSS satellite signals in challenging environments\u201d, Navitec ESA Workshop on Satellite Navigation Technologies and GNSS Signals and Signal Processing, ESTEC, Noordwijk, December 3-5."},{"key":"key2020121721083251600_b29","doi-asserted-by":"crossref","unstructured":"Rainer, S.\n and \n Kenneth, P.\n (1997), \u201cDiffierential evolution \u2013 a simple and efficient heuristic for global optimization over continuous spaces\u201d, \n Journal of Global Optimization\n , Vol. 11 No. 4, pp. 341-359.","DOI":"10.1023\/A:1008202821328"},{"key":"key2020121721083251600_b30","doi-asserted-by":"crossref","unstructured":"Tsui, J.B.\n (2000), \n Fundamentals of Global Positioning System Receivers\n , Wiley-Interscience, NJ.","DOI":"10.1002\/0471200549"},{"key":"key2020121721083251600_b31","doi-asserted-by":"crossref","unstructured":"Van, A.J.M.\n , \n Babu\u0161ka, R.\n and \n De Schutter, B.\n (2009), \u201cNovel ant colony optimization approach to optimal control\u201d, \n International Journal of Intelligent Computing and Cybernetics\n , Vol. 2 No. 3, pp. 414-434.","DOI":"10.1108\/17563780910982671"},{"key":"key2020121721083251600_b32","unstructured":"Van, D.F.\n (2009), \n A-GPS: Assisted GPS\n , GNSS, and SBAS, Artech House, Boston, MA."},{"key":"key2020121721083251600_b35","doi-asserted-by":"crossref","unstructured":"Zhang, S.\n and \n Duan, H.\n (2015), \u201cGaussian pigeon-inspired optimization approach to orbital spacecraft formation reconfiguration\u201d, \n Chinese Journal of Aeronautics\n , Vol. 28 No. 1, pp. 200-205.","DOI":"10.1016\/j.cja.2014.12.008"},{"key":"key2020121721083251600_b36","doi-asserted-by":"crossref","unstructured":"Zhang, W.\n , \n Yu, W.\n and \n Yang, Z.\n (2008), \u201cGenetic and particle swarm algorithm-based optimization solution for high-dimension complex functions\u201d, Fourth International Conference on Natural Computation, 2008 (ICNC\u201908), Vol. 4, pp. 511-515.","DOI":"10.1109\/ICNC.2008.545"},{"key":"key2020121721083251600_b33","doi-asserted-by":"crossref","unstructured":"Zhan, Z.\n , \n Zhang, J.\n , \n Li, Y.\n and \n Liu, H.\n (2012), \u201cA modified brain storm optimization\u201d, IEEE Congress on Evolutionary Computation (CEC) 2012, pp. 1-8.","DOI":"10.1109\/CEC.2012.6256594"},{"key":"key2020121721083251600_b34","doi-asserted-by":"crossref","unstructured":"Zhan, Z.\n , \n Zhang, J.\n , \n Li, Y.\n and \n Shi, Y.\n (2011), \u201cOrthogonal learning particle swarm optimization\u201d, \n IEEE Transactions on Evolutionary Computation\n , Vol. 15 No. 6, pp. 832-847.","DOI":"10.1109\/TEVC.2010.2052054"},{"key":"key2020121721083251600_b38","doi-asserted-by":"crossref","unstructured":"Ziedan, N.I.\n and \n Garrison, J.L.\n (2004), \u201cUnaided acquisition of weak GPS signals using circular correlation or double-block zero padding\u201d, Position Location and Navigation Symposium, pp. 461-470.","DOI":"10.1109\/PLANS.2004.1309030"},{"key":"key2020121721083251600_frd1","doi-asserted-by":"crossref","unstructured":"Borio, D.\n , \n O\u2019driscoll, C.\n and \n Lachapelle, G.\n (2009), \u201cCoherent, noncoherent, and differentially coherent combining techniques for acquisition of new composite GNSS signals\u201d, \n IEEE Transactions on Aerospace and Electronic Systems\n , Vol. 45 No. 3, pp. 1227-1240.","DOI":"10.1109\/TAES.2009.5259196"},{"key":"key2020121721083251600_frd2","doi-asserted-by":"crossref","unstructured":"\u010cern\n and \n Vladimr\n (1985), \u201cThermodynamical approach to the traveling salesman problem: an efficient simulation algorithm\u201d, \n Journal of Optimization Theory and Applications\n , Vol. 45 No. 1, pp. 41-51.","DOI":"10.1007\/BF00940812"},{"key":"key2020121721083251600_frd3","unstructured":"Choi, I.H.\n , \n Park, S.H.\n , \n Cho, D.J.\n , \n Yun, S.J.\n , \n Kim, Y.B.\n and \n Lee, S.J.\n (2001), \u201cA novel weak signal acquisition scheme for assisted GPS\u201d, Proceedings of the 15th International Technical Meeting of the Satellite Division of The Institute of Navigation (ION GPS 2002), pp. 177-183."},{"key":"key2020121721083251600_frd4","doi-asserted-by":"crossref","unstructured":"Eberhart, R.C.\n and \n Kennedy, J.\n (1995), \u201cA new optimizer using particle swarm theory\u201d, Proceedings of the Sixth International Symposium on Micro Machine and Human Science, Vol. 1, pp. 39-43.","DOI":"10.1109\/MHS.1995.494215"},{"key":"key2020121721083251600_frd5","doi-asserted-by":"crossref","unstructured":"Kirkpatrick, S.\n (1984), \u201cOptimization by simulated annealing: quantitative studies\u201d, \n Journal of Statistical Physics\n , Vol. 34 Nos 5-6, pp. 975-986.","DOI":"10.1007\/BF01009452"},{"key":"key2020121721083251600_frd6","doi-asserted-by":"crossref","unstructured":"Zhang, X.\n , \n Duan, H.\n and \n Yang, C.\n (2014), \u201cPigeon-Inspired optimization approach to multiple UAVs formation reconfiguration controller design\u201d, Guidance, Navigation and Control Conference (CGNCC), 2014 IEEE, pp. 2707-2712 (in Chinese).","DOI":"10.1109\/CGNCC.2014.7007594"}],"container-title":["International Journal of Intelligent Computing and Cybernetics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.emeraldinsight.com\/doi\/full-xml\/10.1108\/IJICC-08-2015-0028","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJICC-08-2015-0028\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/IJICC-08-2015-0028\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T22:54:42Z","timestamp":1753397682000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/ijicc\/article\/9\/1\/105-123\/134643"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,3,14]]},"references-count":38,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2016,3,14]]}},"alternative-id":["10.1108\/IJICC-08-2015-0028"],"URL":"https:\/\/doi.org\/10.1108\/ijicc-08-2015-0028","relation":{},"ISSN":["1756-378X"],"issn-type":[{"value":"1756-378X","type":"print"}],"subject":[],"published":{"date-parts":[[2016,3,14]]}}}