{"id":3475,"date":"2025-09-16T16:50:41","date_gmt":"2025-09-16T16:50:41","guid":{"rendered":"https:\/\/172-234-197-23.ip.linodeusercontent.com\/?page_id=3475"},"modified":"2025-09-16T16:50:41","modified_gmt":"2025-09-16T16:50:41","slug":"enhanced-rf-sequence-recovery-comparative-analysis-of-aoa-only-vs-aoatdoa-fusion","status":"publish","type":"page","link":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/?page_id=3475","title":{"rendered":"Enhanced RF Sequence Recovery: Comparative Analysis of AoA-Only vs AoA+TDoA Fusion"},"content":{"rendered":"\n<div data-wp-interactive=\"core\/file\" class=\"wp-block-file\"><object data-wp-bind--hidden=\"!state.hasPdfPreview\" hidden class=\"wp-block-file__embed\" data=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/Enhanced-RF-Sequence-Recovery-Comparative-Analysis-of-AoA-Only-vs-AoATDoA-Fusion-Benjamin-J-Gilbert-College-of-the-Mainland-Robotic-Process-Automation.pdf\" type=\"application\/pdf\" style=\"width:100%;height:600px\" aria-label=\"Embed of Enhanced RF Sequence Recovery Comparative Analysis of AoA-Only vs AoA+TDoA Fusion Benjamin J Gilbert College of the Mainland Robotic Process Automation.\"><\/object><a id=\"wp-block-file--media-83810d61-55c9-4d7b-b07a-1558cb01e89f\" href=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/Enhanced-RF-Sequence-Recovery-Comparative-Analysis-of-AoA-Only-vs-AoATDoA-Fusion-Benjamin-J-Gilbert-College-of-the-Mainland-Robotic-Process-Automation.pdf\">Enhanced RF Sequence Recovery Comparative Analysis of AoA-Only vs AoA+TDoA Fusion Benjamin J Gilbert College of the Mainland Robotic Process Automation<\/a><a href=\"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/wp-content\/uploads\/2025\/09\/Enhanced-RF-Sequence-Recovery-Comparative-Analysis-of-AoA-Only-vs-AoATDoA-Fusion-Benjamin-J-Gilbert-College-of-the-Mainland-Robotic-Process-Automation.pdf\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-83810d61-55c9-4d7b-b07a-1558cb01e89f\">Download<\/a><\/div>\n\n\n\n<p class=\"wp-block-paragraph\">We present a comparative study of grid-based<br>trajectory recovery using angle-of-arrival (AoA) alone versus<br>fused AoA and time-difference-of-arrival (TDoA) observations.<br>Building on our prior AoA-only framework, we integrate TDoA<br>measurements into a discrete beam-search inference pipeline and<br>quantify the resulting gains under sparse and noisy conditions.<br>Across Monte Carlo trials, fusion yields extbf25\u201345% error<br>reduction relative to AoA-only in regimes with limited observation fractions (ho \u2264 0.5) and high AoA noise (\u03c3heta \u2265 10\u25e6<br>),<br>while maintaining robustness to TDoA noise up to extbf100 ns<br>(\u224830 m range). A geometry-based dilution of precision (GDOP)<br>analysis confirms that augmenting AoA with TDoA reduces<br>uncertainty ellipse eccentricity, particularly for non-ideal sensor<br>layouts. Comparisons against baseline extended Kalman and<br>particle filters highlight fusion\u2019s advantages in discrete multihypothesis tracking, with similar accuracy but lower complexity<br>at modest beam widths. Synthetic experiments (100-step trajectories, 3-sensor triangle) demonstrate that AoA+TDoA consistently<br>achieves &lt;300 m mean error under stress conditions where AoAonly exceeds 500 m. These results underscore the operational<br>relevance of multi-modal fusion for electronic warfare and<br>passive geolocation, while motivating future work on real-world<br>validation, synchronization costs, and adaptive fusion strategies.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>We present a comparative study of grid-basedtrajectory recovery using angle-of-arrival (AoA) alone versusfused AoA and time-difference-of-arrival (TDoA) observations.Building on our prior AoA-only framework, we integrate TDoAmeasurements into a discrete beam-search inference pipeline andquantify the resulting gains under sparse and noisy conditions.Across Monte Carlo trials, fusion yields extbf25\u201345% errorreduction relative to AoA-only in regimes with limited&hellip;&nbsp;<\/p>\n","protected":false},"author":2,"featured_media":2058,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"neve_meta_sidebar":"","neve_meta_container":"","neve_meta_enable_content_width":"","neve_meta_content_width":0,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"","footnotes":""},"class_list":["post-3475","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages\/3475","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=3475"}],"version-history":[{"count":0,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/pages\/3475\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=\/wp\/v2\/media\/2058"}],"wp:attachment":[{"href":"https:\/\/neurosphere-2.tail52f848.ts.net\/wordpress\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=3475"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}