Mobility Assisted Wireless Sensor Network Cooperative Localization via SOCP

Yu, Sijia; Su, Xin; Zeng, Jie; Cui, Huanxi

doi:10.1007/978-3-030-05888-3_12

Cited by 2 publications

(6 citation statements)

References 9 publications

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“…Regarding stand-alone positioning in the non-collaborative phase, the most used methods were PDR [ 43 , 63 , 92 , 97 , 98 , 100 , 101 , 102 , 106 , 107 , 110 , 117 , 118 , 120 , 123 , 127 , 128 , 129 , 131 , 141 , 144 , 145 , 146 , 147 ], Ranging [ 42 , 46 , 47 , 81 , 93 , 109 , 111 , 113 , 130 , 132 , 144 , 150 ], RSS-based [ 40 , 41 , 43 , 48 , 77 , 84 , 89 , 103 , 123 , 129 ], k -NN [ 63 , 79 , 108 , 114 , 118 , 119 ,…”

Section: Discussionmentioning

confidence: 99%

“…Another remarkable finding in the non-collaborative part is the lack of details of some key aspects of the CIPSs. Around a third of the reviewed papers did not provide enough details about the method used to provide the position estimate, only being cataloged as fingerprint-based [ 42 , 83 , 98 , 100 , 102 , 143 , 147 , 149 ], ranging [ 42 , 46 , 47 , 81 , 93 , 109 , 111 , 113 , 130 , 132 , 144 , 150 ] and RSS-based [ 40 , 41 , 43 , 48 , 77 , 84 , 89 , 103 , 123 , 129 ] methods. In those works, the authors considered the user’s positioning method in the non-collaborative part irrelevant, i.e., the main focus of the CIPS was to improve the user’s position in the collaborative part, regardless of the approach used in the non-collaborative part.…”

Section: Discussionmentioning

confidence: 99%

“…The study selection process, with step-wise results, is schematically depicted using the PRISMA flow diagram in Figure 2 . As a final set of eligible studies, 84 articles [ 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 63 , 77 , 79 , 80 , 81 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 ,…”

Section: Methodsmentioning

confidence: 99%

“…Algorithm Bayesian F. N/S W/I E PA [ 138 ] UWB UWB TDoA TDoA Coop. Algorithm Analytic N/S W/I E PA [ 137 ] 5G 5G AoA AoA Multilateration LS D I-L S PA+CC [ 49 ] UWB UWB ToA/ToF ToA/ToF Entropy-based ToA LS D I-L S PA+PP [ 81 ] Wi-Fi Wi-Fi RSSI RSSI Ranging Multidimensional Scaling N/S …”

Section: Appendix A1 Search Queriesmentioning

confidence: 99%

“…Note that collaborative approaches should not be confused with data or sensor fusion approaches. Whereas collaborative positioning is focused in systems whose independent actors (users or devices) exchange information and compute relative distances between them to provide the position of the set of users [ 77 , 78 , 79 , 80 , 81 ], sensor fusion combines information from various sensors from a single actor for providing the position of a single user [ 30 , 31 , 32 , 33 ].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Collaborative Indoor Positioning Systems: A Systematic Review

Pascacio

Casteleyn

Torres-Sospedra

et al. 2021

Sensors

109

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Research and development in Collaborative Indoor Positioning Systems (CIPSs) is growing steadily due to their potential to improve on the performance of their non-collaborative counterparts. In contrast to the outdoors scenario, where Global Navigation Satellite System is widely adopted, in (collaborative) indoor positioning systems a large variety of technologies, techniques, and methods is being used. Moreover, the diversity of evaluation procedures and scenarios hinders a direct comparison. This paper presents a systematic review that gives a general view of the current CIPSs. A total of 84 works, published between 2006 and 2020, have been identified. These articles were analyzed and classified according to the described system’s architecture, infrastructure, technologies, techniques, methods, and evaluation. The results indicate a growing interest in collaborative positioning, and the trend tend to be towards the use of distributed architectures and infrastructure-less systems. Moreover, the most used technologies to determine the collaborative positioning between users are wireless communication technologies (Wi-Fi, Ultra-WideBand, and Bluetooth). The predominant collaborative positioning techniques are Received Signal Strength Indication, Fingerprinting, and Time of Arrival/Flight, and the collaborative methods are particle filters, Belief Propagation, Extended Kalman Filter, and Least Squares. Simulations are used as the main evaluation procedure. On the basis of the analysis and results, several promising future research avenues and gaps in research were identified.

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