{"id":{"repo_id":"buffalo","oai_identifier":"oai:ubir.buffalo.edu:10477/80840"},"canonical_url":"https://search.dev.ndltd.org/etd/buffalo/oai:ubir.buffalo.edu:10477/80840","repository":{"repo_id":"buffalo","name":"Buffalo","base_url":"https://ubir.buffalo.edu/oai/request"},"display":{"title":"Enhanced Spatial Smoothing and Coprime Array for Direction of Arrival Estimation","abstract":"M.S.","abstract_html":"M.S.","abstract_has_math":false,"creators":["Srirama reddy Manjuladevi, Shreyas; 0000-0002-5152-4619"],"institution":"State University of New York at Buffalo","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":["Su, Weifeng","Electrical Engineering"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-10-29T16:47:27Z","date_published":"2019-10-29T16:47:27Z","updated_at":"2026-07-27T19:05:25Z","subjects":["engineering"],"languages":["eng"],"rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/10477/80840","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Su, Weifeng","Electrical Engineering"]},{"key":"dc:creator","label":"Author","values":["Srirama reddy Manjuladevi, Shreyas; 0000-0002-5152-4619"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-10-29T16:47:27Z","2019","2019-06-29 16:28:44"]},{"key":"dc:publisher","label":"Institution","values":["State University of New York at Buffalo"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["engineering"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/10477/80840"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["M.S.","Array signal processing is an important branch of signal processing and has attracted a lot of research. The direction of arrival (DOA) estimation is one of the important applications of array signal processing. However, there is a limit on the number of signal sources that an array can identify. In the recent past, there has been an extensive research to increase the number of sources that a given array can identify and to enhance the performance of direction finding algorithms. In this regard, in order to identify more sources than the antennas, coprime array was recently proposed. Also, there are several direction finding algorithms which have been used extensively. One of them is the Multi-Signal Classification (MUSIC) algorithm. However, MUSIC algorithm fails when the signals sources are correlated or coherent to each other. Hence, a pre-processing scheme known as Spatial Smoothing is applied when the incoming signals are correlated or coherent. However, both the coprime array and the Spatial Smoothing MUSIC algorithm can been further enhanced to obtain better and desirable results.In this research, firstly, a modified structure of the coprime array is proposed which has an increased number of Degrees-of-freedom (DOF’s), which in turn increases the number of signal sources that can be identified. The proposed structure has the same number of antennas as the conventional coprime array. Secondly, forward Spatial smoothing is investigated to see if it can be applied to non-uniform antennas. The proposed method shows a better performance than the conventional method, even though the number of signals identified remains the same. The simulation results reflect our claims.Finally, the forward-backward spatial smoothing is discussed, which is an extension of the forward spatial smoothing. The analysis of the singularity of the algorithm is carried out and certain conditions are proposed. If the proposed conditions are satisfied, the K signal sources can be identified by using only 3K/2 antennas. The proposed conditions are supported by numerical results."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Enhanced Spatial Smoothing and Coprime Array for Direction of Arrival Estimation"]}]}],"canonical_facts":{"dc:contributor":["Su, Weifeng","Electrical Engineering"],"dc:creator":["Srirama reddy Manjuladevi, Shreyas; 0000-0002-5152-4619"],"dc:date":["2019-10-29T16:47:27Z","2019","2019-06-29 16:28:44"],"dc:description":["M.S.","Array signal processing is an important branch of signal processing and has attracted a lot of research. The direction of arrival (DOA) estimation is one of the important applications of array signal processing. However, there is a limit on the number of signal sources that an array can identify. In the recent past, there has been an extensive research to increase the number of sources that a given array can identify and to enhance the performance of direction finding algorithms. In this regard, in order to identify more sources than the antennas, coprime array was recently proposed. Also, there are several direction finding algorithms which have been used extensively. One of them is the Multi-Signal Classification (MUSIC) algorithm. However, MUSIC algorithm fails when the signals sources are correlated or coherent to each other. Hence, a pre-processing scheme known as Spatial Smoothing is applied when the incoming signals are correlated or coherent. However, both the coprime array and the Spatial Smoothing MUSIC algorithm can been further enhanced to obtain better and desirable results.In this research, firstly, a modified structure of the coprime array is proposed which has an increased number of Degrees-of-freedom (DOF’s), which in turn increases the number of signal sources that can be identified. The proposed structure has the same number of antennas as the conventional coprime array. Secondly, forward Spatial smoothing is investigated to see if it can be applied to non-uniform antennas. The proposed method shows a better performance than the conventional method, even though the number of signals identified remains the same. The simulation results reflect our claims.Finally, the forward-backward spatial smoothing is discussed, which is an extension of the forward spatial smoothing. The analysis of the singularity of the algorithm is carried out and certain conditions are proposed. If the proposed conditions are satisfied, the K signal sources can be identified by using only 3K/2 antennas. The proposed conditions are supported by numerical results."],"dc:format":["application/pdf"],"dc:identifier":["http://hdl.handle.net/10477/80840"],"dc:language":["eng"],"dc:publisher":["State University of New York at Buffalo"],"dc:rights":["Users of works found in University at Buffalo Institutional Repository (UBIR) are responsible for identifying and contacting the copyright owner for permission to reuse. University at Buffalo Libraries do not manage rights for copyright-protected works and cannot assist with permissions.","Copyright retained by author."],"dc:subject":["engineering"],"dc:title":["Enhanced Spatial Smoothing and Coprime Array for Direction of Arrival Estimation"],"dc:type":["Text","Thesis"]},"updated_at":"2026-07-27T19:05:25Z"}