{"id":"https://openalex.org/W4414539421","doi":"https://doi.org/10.1109/icc52391.2025.11161287","title":"Radar-Driven Occupancy Grid Maps for Robust Perception in Adverse Fog Conditions","display_name":"Radar-Driven Occupancy Grid Maps for Robust Perception in Adverse Fog Conditions","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4414539421","doi":"https://doi.org/10.1109/icc52391.2025.11161287"},"language":"en","primary_location":{"id":"doi:10.1109/icc52391.2025.11161287","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161287","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5106954424","display_name":"Alireza Najafi","orcid":null},"institutions":[{"id":"https://openalex.org/I2801075135","display_name":"Paradise Valley Community College","ror":"https://ror.org/0433rbd97","country_code":"US","type":"education","lineage":["https://openalex.org/I2801075135"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alireza Najafi","raw_affiliation_strings":["University of Ottawa,PARADISE Research Laboratory,EECS,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Ottawa,PARADISE Research Laboratory,EECS,Canada","institution_ids":["https://openalex.org/I2801075135"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001627457","display_name":"Noura Aljeri","orcid":"https://orcid.org/0000-0001-9952-2770"},"institutions":[{"id":"https://openalex.org/I36721946","display_name":"Kuwait University","ror":"https://ror.org/021e5j056","country_code":"KW","type":"education","lineage":["https://openalex.org/I36721946"]}],"countries":["KW"],"is_corresponding":false,"raw_author_name":"Noura AlJeri","raw_affiliation_strings":["Kuwait University,Department of Computer Science,Kuwait"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Kuwait University,Department of Computer Science,Kuwait","institution_ids":["https://openalex.org/I36721946"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012195474","display_name":"Azzedine Boukerche","orcid":"https://orcid.org/0000-0002-3851-9938"},"institutions":[{"id":"https://openalex.org/I2801075135","display_name":"Paradise Valley Community College","ror":"https://ror.org/0433rbd97","country_code":"US","type":"education","lineage":["https://openalex.org/I2801075135"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Azzedine Boukerche","raw_affiliation_strings":["University of Ottawa,PARADISE Research Laboratory,EECS,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Ottawa,PARADISE Research Laboratory,EECS,Canada","institution_ids":["https://openalex.org/I2801075135"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.4653,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.95593971,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"4251","last_page":"4256"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9948999881744385,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9897000193595886,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.983299970626831,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.7840999960899353},{"id":"https://openalex.org/keywords/occupancy-grid-mapping","display_name":"Occupancy grid mapping","score":0.7522000074386597},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7109000086784363},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.5861999988555908},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5385000109672546},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5274999737739563},{"id":"https://openalex.org/keywords/occupancy","display_name":"Occupancy","score":0.501800000667572},{"id":"https://openalex.org/keywords/radar","display_name":"Radar","score":0.49070000648498535}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7840999960899353},{"id":"https://openalex.org/C57077369","wikidata":"https://www.wikidata.org/wiki/Q7075747","display_name":"Occupancy grid mapping","level":4,"score":0.7522000074386597},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7109000086784363},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6700999736785889},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.5861999988555908},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5385000109672546},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5274999737739563},{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.501800000667572},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.49070000648498535},{"id":"https://openalex.org/C2992147540","wikidata":"https://www.wikidata.org/wiki/Q1277161","display_name":"Adverse weather","level":2,"score":0.4205000102519989},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.38280001282691956},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.367000013589859},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3549000024795532},{"id":"https://openalex.org/C156172958","wikidata":"https://www.wikidata.org/wiki/Q3438407","display_name":"Grid reference","level":4,"score":0.3497999906539917},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3303000032901764},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.32260000705718994},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3061000108718872},{"id":"https://openalex.org/C2778562939","wikidata":"https://www.wikidata.org/wiki/Q1298791","display_name":"Synchronization (alternating current)","level":3,"score":0.29820001125335693},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C32283439","wikidata":"https://www.wikidata.org/wiki/Q1407014","display_name":"Radar tracker","level":3,"score":0.25220000743865967},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.25200000405311584},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.25110000371932983},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.25049999356269836}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icc52391.2025.11161287","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icc52391.2025.11161287","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ICC 2025 - IEEE International Conference on Communications","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W2145889067","https://openalex.org/W2193145675","https://openalex.org/W2953399169","https://openalex.org/W2963037989","https://openalex.org/W2963041685","https://openalex.org/W2968296999","https://openalex.org/W2970475272","https://openalex.org/W2971170254","https://openalex.org/W2971197296","https://openalex.org/W3008115128","https://openalex.org/W3034543232","https://openalex.org/W3035346742","https://openalex.org/W3035574168","https://openalex.org/W3090139470","https://openalex.org/W3167214600","https://openalex.org/W3176821088","https://openalex.org/W3191343975","https://openalex.org/W3209639308","https://openalex.org/W4225793049","https://openalex.org/W4226290276","https://openalex.org/W4312501532","https://openalex.org/W4312707458","https://openalex.org/W4313162344","https://openalex.org/W4383066393"],"related_works":[],"abstract_inverted_index":{"Adverse":[0],"weather":[1,43],"conditions":[2,21],"significantly":[3],"challenge":[4],"scene":[5],"understanding":[6],"of":[7,19,38,95],"autonomous":[8],"vehicles":[9],"by":[10],"degrading":[11],"perception":[12],"system":[13],"performance.":[14],"Despite":[15],"advancements,":[16],"the":[17,36,57,93,96],"impacts":[18],"such":[20],"still":[22],"require":[23],"further":[24],"investigation.":[25],"In":[26],"this":[27],"paper,":[28],"we":[29],"propose":[30],"a":[31],"novel":[32],"approach":[33],"that":[34],"leverages":[35],"advantages":[37],"Radar":[39,54],"sensors":[40],"against":[41],"various":[42,103],"types":[44],"to":[45,61,81],"improve":[46],"robustness":[47,112],"under":[48,102],"foggy":[49],"weather.":[50],"Our":[51],"framework":[52,91],"refines":[53],"measurements":[55],"through":[56],"Bayesian":[58],"Filtering":[59],"algorithm":[60],"enhance":[62],"data":[63,101],"quality":[64],"and":[65,92,113],"sparsity,":[66],"generating":[67],"informative":[68],"representations":[69],"as":[70],"probabilistic":[71],"Occupancy":[72],"Grid":[73],"Maps":[74],"(OGM).":[75],"We":[76,88],"address":[77],"sensor":[78],"synchronization":[79],"challenges":[80],"ensure":[82],"accurate":[83],"fusion":[84],"across":[85],"different":[86],"modalities.":[87],"evaluate":[89],"our":[90],"effectiveness":[94],"OGMs":[97],"fused":[98],"with":[99,119],"LiDAR":[100],"fog":[104],"densities.":[105],"The":[106],"experimental":[107],"results":[108],"demonstrated":[109],"improvements":[110],"in":[111],"reduced":[114],"detection":[115],"errors":[116],"when":[117],"compared":[118],"LiDAR-only":[120],"object":[121],"detection.":[122]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
