{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/38631"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/38631","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Multisensor track initiation method that addresses the missing measurement problem","abstract":"A method for integrating multisensor data for the purpose of track initiation using horizon infrared and radar data is proposed. This multisensor track initiation (MSTI) method extends contemporary data fusion techniques so as to address the problem of missing measurements. The missing measurement phenomenon occurs due to a variety of reasons, the foremost of which is variation in sensor detection performance due to environmental factors. The proposed MSTI method requires only the results of spatial feature tests that are performed on sensor data sequences. The formation of data sequences and the derivation of feature tests to integrate horizon radar and infrared data of differing resolutions is addressed. Results are presented that detail the performance of the MSTI technique when operating on simulated data. It is shown that the statistical performance of the MSTI technique is better than or equal to that of the AND algorithm for a representative set of scenarios. The sensitivity of the MSTI method to variations in assumed feature test and data sequence statistics is also addressed.","abstract_html":"A method for integrating multisensor data for the purpose of track initiation using horizon infrared and radar data is proposed. This multisensor track initiation (MSTI) method extends contemporary data fusion techniques so as to address the problem of missing measurements. The missing measurement phenomenon occurs due to a variety of reasons, the foremost of which is variation in sensor detection performance due to environmental factors. The proposed MSTI method requires only the results of spatial feature tests that are performed on sensor data sequences. The formation of data sequences and the derivation of feature tests to integrate horizon radar and infrared data of differing resolutions is addressed. Results are presented that detail the performance of the MSTI technique when operating on simulated data. It is shown that the statistical performance of the MSTI technique is better than or equal to that of the AND algorithm for a representative set of scenarios. The sensitivity of the MSTI method to variations in assumed feature test and data sequence statistics is also addressed.","abstract_has_math":false,"creators":["Pawlak, Robert James"],"institution":"Virginia Tech","degree_name":"Ph. D.","degree_level":"doctoral","degree_discipline":"Electrical Engineering","degree_department":"Electrical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Beex, Aloysius A."],"committee_members":["Brown, Gary","Conners, Richard W.","Pratt, Timothy","Royce, G.A."],"year":1992,"date_issued":"1992","date_published":"1992","updated_at":"2026-07-22T22:19:39Z","subjects":[],"languages":["en"],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-06192006-125725"],"render_values":[{"text":"etd-06192006-125725","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/38631","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Beex, Aloysius A."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Brown, Gary","Conners, Richard W.","Pratt, Timothy","Royce, G.A."]},{"key":"dc:contributor.department","label":"Department","values":["Electrical Engineering"]},{"key":"dc:creator","label":"Author","values":["Pawlak, Robert James"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T21:15:06Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T21:15:06Z","2006-06-19"]},{"key":"dc:date.issued","label":"Date","values":["1992"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Dissertation"]},{"key":"dc:type.dcmitype","label":"Dc Type Dcmitype","values":["Text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["doctoral"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph. D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-06192006-125725"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/38631"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["A method for integrating multisensor data for the purpose of track initiation using horizon infrared and radar data is proposed. This multisensor track initiation (MSTI) method extends contemporary data fusion techniques so as to address the problem of missing measurements. The missing measurement phenomenon occurs due to a variety of reasons, the foremost of which is variation in sensor detection performance due to environmental factors. The proposed MSTI method requires only the results of spatial feature tests that are performed on sensor data sequences. The formation of data sequences and the derivation of feature tests to integrate horizon radar and infrared data of differing resolutions is addressed. Results are presented that detail the performance of the MSTI technique when operating on simulated data. It is shown that the statistical performance of the MSTI technique is better than or equal to that of the AND algorithm for a representative set of scenarios. The sensitivity of the MSTI method to variations in assumed feature test and data sequence statistics is also addressed."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["Ph. D."]},{"key":"dc:format.medium","label":"Dc Format Medium","values":["BTD"]},{"key":"dc:format.mimetype","label":"Dc Format Mimetype","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Multisensor track initiation method that addresses the missing measurement problem"]}]}],"canonical_facts":{"dc:contributor.committeechair":["Beex, Aloysius A."],"dc:contributor.committeemember":["Brown, Gary","Conners, Richard W.","Pratt, Timothy","Royce, G.A."],"dc:contributor.department":["Electrical Engineering"],"dc:creator":["Pawlak, Robert James"],"dc:date.accessioned":["2014-03-14T21:15:06Z"],"dc:date.available":["2014-03-14T21:15:06Z","2006-06-19"],"dc:date.issued":["1992"],"dc:description.abstract":["A method for integrating multisensor data for the purpose of track initiation using horizon infrared and radar data is proposed. This multisensor track initiation (MSTI) method extends contemporary data fusion techniques so as to address the problem of missing measurements. The missing measurement phenomenon occurs due to a variety of reasons, the foremost of which is variation in sensor detection performance due to environmental factors. The proposed MSTI method requires only the results of spatial feature tests that are performed on sensor data sequences. The formation of data sequences and the derivation of feature tests to integrate horizon radar and infrared data of differing resolutions is addressed. Results are presented that detail the performance of the MSTI technique when operating on simulated data. It is shown that the statistical performance of the MSTI technique is better than or equal to that of the AND algorithm for a representative set of scenarios. The sensitivity of the MSTI method to variations in assumed feature test and data sequence statistics is also addressed."],"dc:description.degree":["Ph. D."],"dc:format.medium":["BTD"],"dc:format.mimetype":["application/pdf"],"dc:identifier.other":["etd-06192006-125725"],"dc:identifier.uri":["http://hdl.handle.net/10919/38631"],"dc:language.iso":["en"],"dc:publisher":["Virginia Tech"],"dc:rights":["In Copyright"],"dc:rights.uri":["http://rightsstatements.org/vocab/InC/1.0/"],"dc:title":["Multisensor track initiation method that addresses the missing measurement problem"],"dc:type":["Dissertation"],"dc:type.dcmitype":["Text"],"thesis:degree_discipline":["Electrical Engineering"],"thesis:degree_level":["doctoral"],"thesis:degree_name":["Ph. D."],"thesis:institution_name":["Virginia Polytechnic Institute and State University"]},"updated_at":"2026-07-22T22:19:39Z"}