Navigation in GPS Spoofed Environment Using M-Best Positioning Algorithm and Data Association Article Swipe
Bethi Pardhasaradhi
,
Pathipati Srihari
,
P. Aparna
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/access.2021.3064383
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1109/access.2021.3064383
Intentionally misguiding a global positioning system (GPS) receiver has become a potential threat to almost all civilian GPS receivers in recent years. GPS spoofing is among the types of intentional interference, in which a spoofing device transmits spoofed signals towards the GPS receiver to alter the GPS positioning information. This paper presents a robust positioning algorithm, followed by a track filter, to mitigate the effects of spoofing. It is proposed to accept the authentic GPS signals and spoofed GPS signals into the positioning algorithm and perform the robust positioning with all possible combinations of authentic and spoofed pseudorange measurements. The pseudorange positioning algorithm is accomplished using an iterative least squares (ILS). Further, to efficiently represent the robust algorithm, the M-best position algorithm is proposed, in which a likelihood-based cost function optimizes the positions and only provides M-best positions at a given epoch. However, during robust positioning, the positions evolved due to spoofed pseudorange measurements are removed to overcome GPS spoofing. In order to remove the fake positions being evolved owing to wrong measurement associations in the ILS, a gating technique is applied within the Kalman filter (KF) framework. The navigation filter is a three-dimensional KF with a constant velocity (CV) model, all the position estimates evolved at a specific epoch are observations. Besides, to enhance this technique’s performance, the track to position association is performed by using two data association algorithms: nearest neighbor (NN) and probabilistic data association (PDA). Simulations are carried out for GPS receiver positioning by injecting different combinations of spoofed signals into the receiver. The proposed algorithm’s efficiency is given by a success rate metric (defined as the navigation track to follow the true trajectory rather than spoofing trajectory) and position root mean square error (PRMSE).
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2021.3064383
- OA Status
- gold
- Cited By
- 23
- References
- 48
- Related Works
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- OpenAlex ID
- https://openalex.org/W3135284787
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3135284787Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2021.3064383Digital Object Identifier
- Title
-
Navigation in GPS Spoofed Environment Using M-Best Positioning Algorithm and Data AssociationWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2021Year of publication
- Publication date
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2021-01-01Full publication date if available
- Authors
-
Bethi Pardhasaradhi, Pathipati Srihari, P. AparnaList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2021.3064383Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1109/access.2021.3064383Direct OA link when available
- Concepts
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Pseudorange, Spoofing attack, Global Positioning System, Computer science, Algorithm, Kalman filter, Real-time computing, GNSS applications, Artificial intelligence, Telecommunications, Computer securityTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
23Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 5, 2024: 6, 2023: 3, 2022: 5, 2021: 4Per-year citation counts (last 5 years)
- References (count)
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48Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.GPS | 17, 22, 41, 46, 74, 78, 158, 244 |
| abstract_inverted_index.The | 99, 188, 257 |
| abstract_inverted_index.all | 15, 90, 201 |
| abstract_inverted_index.and | 76, 84, 95, 133, 234, 282 |
| abstract_inverted_index.are | 154, 210, 240 |
| abstract_inverted_index.due | 149 |
| abstract_inverted_index.for | 243 |
| abstract_inverted_index.has | 8 |
| abstract_inverted_index.out | 242 |
| abstract_inverted_index.the | 26, 40, 45, 63, 72, 81, 86, 115, 118, 131, 146, 164, 175, 183, 202, 218, 255, 270, 275 |
| abstract_inverted_index.two | 227 |
| abstract_inverted_index.(CV) | 199 |
| abstract_inverted_index.(KF) | 186 |
| abstract_inverted_index.(NN) | 233 |
| abstract_inverted_index.ILS, | 176 |
| abstract_inverted_index.This | 49 |
| abstract_inverted_index.cost | 128 |
| abstract_inverted_index.data | 228, 236 |
| abstract_inverted_index.fake | 165 |
| abstract_inverted_index.into | 80, 254 |
| abstract_inverted_index.mean | 285 |
| abstract_inverted_index.only | 134 |
| abstract_inverted_index.rate | 266 |
| abstract_inverted_index.root | 284 |
| abstract_inverted_index.than | 279 |
| abstract_inverted_index.this | 215 |
| abstract_inverted_index.true | 276 |
| abstract_inverted_index.with | 89, 195 |
| abstract_inverted_index.(GPS) | 6 |
| abstract_inverted_index.alter | 44 |
| abstract_inverted_index.among | 25 |
| abstract_inverted_index.being | 167 |
| abstract_inverted_index.epoch | 209 |
| abstract_inverted_index.error | 287 |
| abstract_inverted_index.given | 140, 262 |
| abstract_inverted_index.least | 108 |
| abstract_inverted_index.order | 161 |
| abstract_inverted_index.owing | 169 |
| abstract_inverted_index.paper | 50 |
| abstract_inverted_index.track | 59, 219, 272 |
| abstract_inverted_index.types | 27 |
| abstract_inverted_index.using | 105, 226 |
| abstract_inverted_index.which | 32, 125 |
| abstract_inverted_index.wrong | 171 |
| abstract_inverted_index.(ILS). | 110 |
| abstract_inverted_index.(PDA). | 238 |
| abstract_inverted_index.Kalman | 184 |
| abstract_inverted_index.M-best | 119, 136 |
| abstract_inverted_index.accept | 71 |
| abstract_inverted_index.almost | 14 |
| abstract_inverted_index.become | 9 |
| abstract_inverted_index.device | 35 |
| abstract_inverted_index.during | 143 |
| abstract_inverted_index.epoch. | 141 |
| abstract_inverted_index.filter | 185, 190 |
| abstract_inverted_index.follow | 274 |
| abstract_inverted_index.gating | 178 |
| abstract_inverted_index.global | 3 |
| abstract_inverted_index.metric | 267 |
| abstract_inverted_index.model, | 200 |
| abstract_inverted_index.rather | 278 |
| abstract_inverted_index.recent | 20 |
| abstract_inverted_index.remove | 163 |
| abstract_inverted_index.robust | 53, 87, 116, 144 |
| abstract_inverted_index.square | 286 |
| abstract_inverted_index.system | 5 |
| abstract_inverted_index.threat | 12 |
| abstract_inverted_index.within | 182 |
| abstract_inverted_index.years. | 21 |
| abstract_inverted_index.applied | 181 |
| abstract_inverted_index.carried | 241 |
| abstract_inverted_index.effects | 64 |
| abstract_inverted_index.enhance | 214 |
| abstract_inverted_index.evolved | 148, 168, 205 |
| abstract_inverted_index.filter, | 60 |
| abstract_inverted_index.nearest | 231 |
| abstract_inverted_index.perform | 85 |
| abstract_inverted_index.removed | 155 |
| abstract_inverted_index.signals | 38, 75, 79, 253 |
| abstract_inverted_index.spoofed | 37, 77, 96, 151, 252 |
| abstract_inverted_index.squares | 109 |
| abstract_inverted_index.success | 265 |
| abstract_inverted_index.towards | 39 |
| abstract_inverted_index.(PRMSE). | 288 |
| abstract_inverted_index.(defined | 268 |
| abstract_inverted_index.Besides, | 212 |
| abstract_inverted_index.Further, | 111 |
| abstract_inverted_index.However, | 142 |
| abstract_inverted_index.civilian | 16 |
| abstract_inverted_index.constant | 197 |
| abstract_inverted_index.followed | 56 |
| abstract_inverted_index.function | 129 |
| abstract_inverted_index.mitigate | 62 |
| abstract_inverted_index.neighbor | 232 |
| abstract_inverted_index.overcome | 157 |
| abstract_inverted_index.position | 120, 203, 221, 283 |
| abstract_inverted_index.possible | 91 |
| abstract_inverted_index.presents | 51 |
| abstract_inverted_index.proposed | 69, 258 |
| abstract_inverted_index.provides | 135 |
| abstract_inverted_index.receiver | 7, 42, 245 |
| abstract_inverted_index.specific | 208 |
| abstract_inverted_index.spoofing | 23, 34, 280 |
| abstract_inverted_index.velocity | 198 |
| abstract_inverted_index.algorithm | 83, 102, 121 |
| abstract_inverted_index.authentic | 73, 94 |
| abstract_inverted_index.different | 249 |
| abstract_inverted_index.estimates | 204 |
| abstract_inverted_index.injecting | 248 |
| abstract_inverted_index.iterative | 107 |
| abstract_inverted_index.optimizes | 130 |
| abstract_inverted_index.performed | 224 |
| abstract_inverted_index.positions | 132, 137, 147, 166 |
| abstract_inverted_index.potential | 11 |
| abstract_inverted_index.proposed, | 123 |
| abstract_inverted_index.receiver. | 256 |
| abstract_inverted_index.receivers | 18 |
| abstract_inverted_index.represent | 114 |
| abstract_inverted_index.spoofing. | 66, 159 |
| abstract_inverted_index.technique | 179 |
| abstract_inverted_index.transmits | 36 |
| abstract_inverted_index.algorithm, | 55, 117 |
| abstract_inverted_index.efficiency | 260 |
| abstract_inverted_index.framework. | 187 |
| abstract_inverted_index.misguiding | 1 |
| abstract_inverted_index.navigation | 189, 271 |
| abstract_inverted_index.trajectory | 277 |
| abstract_inverted_index.Simulations | 239 |
| abstract_inverted_index.algorithms: | 230 |
| abstract_inverted_index.association | 222, 229, 237 |
| abstract_inverted_index.efficiently | 113 |
| abstract_inverted_index.intentional | 29 |
| abstract_inverted_index.measurement | 172 |
| abstract_inverted_index.positioning | 4, 47, 54, 82, 88, 101, 246 |
| abstract_inverted_index.pseudorange | 97, 100, 152 |
| abstract_inverted_index.trajectory) | 281 |
| abstract_inverted_index.accomplished | 104 |
| abstract_inverted_index.associations | 173 |
| abstract_inverted_index.combinations | 92, 250 |
| abstract_inverted_index.information. | 48 |
| abstract_inverted_index.measurements | 153 |
| abstract_inverted_index.performance, | 217 |
| abstract_inverted_index.positioning, | 145 |
| abstract_inverted_index.Intentionally | 0 |
| abstract_inverted_index.interference, | 30 |
| abstract_inverted_index.measurements. | 98 |
| abstract_inverted_index.observations. | 211 |
| abstract_inverted_index.probabilistic | 235 |
| abstract_inverted_index.likelihood-based | 127 |
| abstract_inverted_index.three-dimensional | 193 |
| abstract_inverted_index.algorithm’s | 259 |
| abstract_inverted_index.technique’s | 216 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 96 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.91049871 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | True |