{"id":"https://openalex.org/W3157201576","doi":"https://doi.org/10.1109/taes.2021.3075533","title":"Conditionally Markov Modeling and Optimal Estimation for Trajectory With Waypoints and Destination","display_name":"Conditionally Markov Modeling and Optimal Estimation for Trajectory With Waypoints and Destination","publication_year":2021,"publication_date":"2021-05-04","ids":{"openalex":"https://openalex.org/W3157201576","doi":"https://doi.org/10.1109/taes.2021.3075533","mag":"3157201576"},"language":"en","primary_location":{"id":"doi:10.1109/taes.2021.3075533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2021.3075533","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Aerospace and Electronic Systems","raw_type":"journal-article"},"type":"article","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/A5031408792","display_name":"Reza Rezaie","orcid":"https://orcid.org/0000-0002-1204-4794"},"institutions":[{"id":"https://openalex.org/I192396691","display_name":"University of New Orleans","ror":"https://ror.org/034mtvk83","country_code":"US","type":"education","lineage":["https://openalex.org/I192396691","https://openalex.org/I2799628689"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Reza Rezaie","raw_affiliation_strings":["University of New Orleans, New Orleans, LA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1204-4794","affiliations":[{"raw_affiliation_string":"University of New Orleans, New Orleans, LA, USA","institution_ids":["https://openalex.org/I192396691"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066692075","display_name":"X. Rong Li","orcid":"https://orcid.org/0000-0001-6594-5919"},"institutions":[{"id":"https://openalex.org/I192396691","display_name":"University of New Orleans","ror":"https://ror.org/034mtvk83","country_code":"US","type":"education","lineage":["https://openalex.org/I192396691","https://openalex.org/I2799628689"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"X. Rong Li","raw_affiliation_strings":["University of New Orleans, New Orleans, LA, USA"],"raw_orcid":"https://orcid.org/0000-0001-6594-5919","affiliations":[{"raw_affiliation_string":"University of New Orleans, New Orleans, LA, USA","institution_ids":["https://openalex.org/I192396691"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071755646","display_name":"Vesselin P. Jilkov","orcid":"https://orcid.org/0000-0002-2968-4288"},"institutions":[{"id":"https://openalex.org/I192396691","display_name":"University of New Orleans","ror":"https://ror.org/034mtvk83","country_code":"US","type":"education","lineage":["https://openalex.org/I192396691","https://openalex.org/I2799628689"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vesselin P. Jilkov","raw_affiliation_strings":["University of New Orleans, New Orleans, LA, USA"],"raw_orcid":"https://orcid.org/0000-0002-2968-4288","affiliations":[{"raw_affiliation_string":"University of New Orleans, New Orleans, LA, USA","institution_ids":["https://openalex.org/I192396691"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I192396691"],"apc_list":null,"apc_paid":null,"fwci":2.1352,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.92153324,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"57","issue":"4","first_page":"2006","last_page":"2020"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11489","display_name":"Air Traffic Management and Optimization","score":0.9991000294685364,"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/T11489","display_name":"Air Traffic Management and Optimization","score":0.9991000294685364,"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T11622","display_name":"Maritime Navigation and Safety","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.8790996074676514},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.6651954054832458},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6024599671363831},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.5842399001121521},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.561978816986084},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.5537207126617432},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.5477021932601929},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4776138961315155},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3624366223812103},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24533212184906006},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1314454972743988},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.11709082126617432},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07992285490036011},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07686564326286316}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.8790996074676514},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.6651954054832458},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6024599671363831},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.5842399001121521},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.561978816986084},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.5537207126617432},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.5477021932601929},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4776138961315155},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3624366223812103},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24533212184906006},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1314454972743988},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.11709082126617432},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07992285490036011},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07686564326286316},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taes.2021.3075533","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taes.2021.3075533","pdf_url":null,"source":{"id":"https://openalex.org/S193624734","display_name":"IEEE Transactions on Aerospace and Electronic Systems","issn_l":"0018-9251","issn":["0018-9251","1557-9603","2371-9877"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Aerospace and Electronic Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G346861580","display_name":"AIR TRAFFIC DEMAND IN THE NATIONAL AIRSPACE SYSTEMS (NAS) HAS BEEN FORECAST TO DOUBLE BY THE YEAR 2025.  UNFORTUNATELY  THE PRESENT AIR TRAFFIC CONTROL (ATC) SYSTEM IS ALREADY STRAINED AND CANNOT SCALE TO MEET THIS DEMAND. MOREOVER  WITH THE ADVENT OF UNMANNED AERIAL SYSTEMS SHARING NAS  THE SITUATION MAY DETERIORATE EVEN MORE RAPIDLY. TO RESTRUCTURE THE ATC SYSTEM  NASA IS COOPERATINGWITH THE FEDERAL AVIATION ADMINISTRATION AS WELL AS OTHER GOVERNMENT AGENCIES TO DEVELOP NEXTGEN  DESIGNED TO GREATLY INCREASE THE NAS CAPACITY  EFFICIENCY  SAFETY  FLEXIBILITY  AND ENVIRONMENTAL PROTECTION. HOWEVER  WHAT IS NEEDED IS A TRANSFORMATION FROM ATC TO AIR TRAFFIC MANAGEMENT (ATM)  ALLOWING AIRCRAFT MORE AUTONOMY. DEVELOPING MAJOR COMPONENTS OF THAT TRANSFORMATIONAL SYSTEM IS THE OVERALL GOAL OF THIS PROJECT  WHICH IS COORDINATED BY SCIENCE PI X. RONG LI  UNIVERSITY OF NEW ORLEANS. THE TEAM INVOLVES RESEARCHERS AT LSU AND SU AS WELL AS SUPPORT FROM AMES  LARC  SIX BUSINESS/INDUSTRY CONCERNS PLUS THE U.S. AIR FORCEAND THE DEPARTMENT OF ENERGY. AN ATM SYSTEM IS CENTERED ON TRAJECTORY-BASED OPERATIONS  WHICH RELY CRITICALLY ON RELIABLE AND ACCURATE INFORMATION PROCESSING AND NETWORK-CENTRIC MANAGEMENT. THIS INCLUDES 4D TRAJECTORY PREDICTION (TP)  INTENT INFERENCE AND VERIFICATION (IIV)  CONFLICT DETECTION AND RESOLUTION (CDR)  SEPARATION ASSURANCE (SA)  CONFORMANCE MONITORING (CM)  AND AIRCRAFT HEALTH MANAGEMENT. EACH OF THESE REPRESENTS A SEPARATE OPERATIONAL PROBLEM FOR WHICH WE PROPOSE INNOVATIVE AND SOLID FORMULATIONS OF THE PROBLEM  SYSTEMATIC AND PROMISING SOLUTION APPROACHES  AND WELL-THOUGHT-OUT RESEARCH TASKS. FOR EXAMPLE  ACCURATE AND RELIABLE LONG-TERM TP AND IIV CAN ONLY COME HAND IN HAND  SINCE THEY INVOLVE AIRCRAFT INTENT  WEATHER CONDITIONS  NAVIGATION ACCURACY  ETC. OURAPPROACH IS BASED ON JOINT DECISION AND ESTIMATION  A FRAMEWORK WE DEVELOPED RECENTLY  ALONG WITH ITS OPTIMAL SOLUTION. SIMILARLY  OUR PROPOSED STATISTICAL CDR REPRESENTS A NOVEL APPROACH OFFERING CONFLICT ALERTS AT DIFFERENT LEVELS BASED ON A DIRECT STATISTICAL HYPOTHESISTESTING FORMULATION  WHICH WILL BE MORE CONVENIENT TO USE THAN MOST EXISTING MODELS. A PRIMARY TASK IS TO COMBINE THE SOLUTIONS INTO A MULTI-AGENT SYSTEM (MAS) APPROACH TO ATM. WE PROPOSE TO FULLY ACCOUNT FOR THE HETEROGENEITY OF THE INDIVIDUAL SYSTEMS AND CONTROLLERS  AND TO TAKE INTO ACCOUNT THE PRACTICAL COMMUNICATION CONSTRAINTS. THE MERIT OF THIS PROJECT IS FOURFOLD. FIRST  THE RESEARCHTOPICS HAVE GREAT IMPORTANCE FOR NEXTGEN; SECOND  THE RESEARCH PLANS ARE WELL DEVELOPED; THIRD  THE TEAM IS UNIQUELY QUALIFIED FOR THE WORK; AND FOURTH THE RESULTS WILL BOOST LOUISIANA S INVESTMENT IN THIS FIELD AND MAKE A MAJOR CONTRIBUTION TO NASA AERONAUTICS.","funder_award_id":"NNX13AD29A","funder_id":"https://openalex.org/F4320306101","funder_display_name":"National Aeronautics and Space Administration"}],"funders":[{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W2006866209","https://openalex.org/W2080947828","https://openalex.org/W2140242774","https://openalex.org/W2145377510","https://openalex.org/W2146243646","https://openalex.org/W2146705677","https://openalex.org/W2148474843","https://openalex.org/W2160664904","https://openalex.org/W2160920523","https://openalex.org/W2169030242","https://openalex.org/W2219299986","https://openalex.org/W2312311608","https://openalex.org/W2321767198","https://openalex.org/W2328413619","https://openalex.org/W2331083093","https://openalex.org/W2511571189","https://openalex.org/W2572270144","https://openalex.org/W2577278316","https://openalex.org/W2594388303","https://openalex.org/W2595142274","https://openalex.org/W2615360983","https://openalex.org/W2775541648","https://openalex.org/W2790115023","https://openalex.org/W2796839834","https://openalex.org/W2895874880","https://openalex.org/W2899765703","https://openalex.org/W2901325619","https://openalex.org/W2904211149","https://openalex.org/W2939984110","https://openalex.org/W2946793658","https://openalex.org/W2954082053","https://openalex.org/W2963781522","https://openalex.org/W2995384287","https://openalex.org/W3156367664","https://openalex.org/W4240790602","https://openalex.org/W6700701042"],"related_works":["https://openalex.org/W2379651310","https://openalex.org/W1541249122","https://openalex.org/W2084326697","https://openalex.org/W2113019827","https://openalex.org/W2027903142","https://openalex.org/W2354322608","https://openalex.org/W2186675474","https://openalex.org/W2387462590","https://openalex.org/W2056274461","https://openalex.org/W2077211377"],"abstract_inverted_index":{"On":[0,55],"a":[1,12,17,29,40,74,99,116,121],"grand":[2],"scale,":[3],"motion":[4],"trajectories":[5,109],"are":[6,70,184],"usually":[7],"defined":[8],"by":[9,82],"an":[10,32],"origin,":[11,43,85],"sequence":[13,119],"of":[14,101,136,148,163],"waypoints,":[15,45,86],"and":[16,37,46,64,67,87,177],"destination.":[18,41],"A":[19],"typical":[20],"example":[21],"is":[22],"in":[23,73,91,140],"air":[24],"traffic":[25],"management":[26],"(ATM),":[27],"where":[28],"flight":[30,75],"from":[31,154],"origin":[33],"passes":[34],"several":[35],"waypoints":[36],"arrives":[38],"at":[39],"The":[42],"the":[44,47,56,84,141,149,161,164],"destination":[48,88],"contain":[49],"useful":[50],"information":[51],"for":[52,129,168,179],"trajectory":[53,61,92,169],"modeling.":[54,93,170],"other":[57],"hand,":[58],"due":[59],"to":[60,106],"design":[62],"criteria":[63],"ATM":[65],"restrictions":[66],"requirements,":[68],"there":[69],"long-range":[71,111],"dependencies":[72,78],"trajectory.":[76],"Such":[77],"can":[79,151],"be":[80,152],"modeled":[81],"taking":[83],"into":[89],"account":[90],"In":[94,171],"this":[95],"article,":[96],"we":[97,114,124,173],"propose":[98],"class":[100],"conditionally":[102],"Markov":[103],"(CM)":[104],"sequences":[105,139],"model":[107],"such":[108],"with":[110],"dependencies.":[112],"First,":[113],"define":[115],"general":[117],"CM":[118,138,166],"as":[120],"foundation.":[122],"Then,":[123],"discuss":[125],"its":[126],"special":[127],"cases":[128],"different":[130,180],"scenarios.":[131],"We":[132,144,158],"derive":[133],"dynamic":[134],"models":[135,150,167],"these":[137],"Gaussian":[142],"case.":[143],"show":[145],"how":[146],"parameters":[147],"learned":[153],"data":[155],"or":[156],"designed.":[157],"also":[159],"justify":[160],"use":[162],"proposed":[165],"addition,":[172],"obtain":[174],"optimal":[175],"filters":[176],"predictors":[178],"models.":[181],"Simulation":[182],"demonstrations":[183],"given.":[185]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
