{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2015:44UBBXJNTE6G6LVWYNS2B2MK7D","short_pith_number":"pith:44UBBXJN","schema_version":"1.0","canonical_sha256":"e72810dd2d993c6f2eb6c365a0e98af8f91b4fa8a8d76b9046eb39dcdfa3f7bd","source":{"kind":"arxiv","id":"1507.05266","version":1},"attestation_state":"computed","paper":{"title":"A Unifying Framework for Adaptive Radar Detection in Homogeneous plus Structured Interference-Part II: Detectors Design","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","stat.ME"],"primary_cat":"cs.IT","authors_text":"Antonio De Maio, Danilo Orlando, Domenico Ciuonzo","submitted_at":"2015-07-19T09:23:10Z","abstract_excerpt":"This paper deals with the problem of adaptive multidimensional/multichannel signal detection in homogeneous Gaussian disturbance with unknown covariance matrix and structured (unknown) deterministic interference. The aforementioned problem extends the well-known Generalized Multivariate Analysis of Variance (GMANOVA) tackled in the open literature. In a companion paper, we have obtained the Maximal Invariant Statistic (MIS) for the problem under consideration, as an enabling tool for the design of suitable detectors which possess the Constant False-Alarm Rate (CFAR) property. Herein, we focus "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1507.05266","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2015-07-19T09:23:10Z","cross_cats_sorted":["math.IT","stat.ME"],"title_canon_sha256":"9c6024841f3ffe0311d3b1d97c9cebe33a3a02a679aff2e6d3631ce6bfb241d3","abstract_canon_sha256":"f9edcfa79b60b2f8ab5cb68de687ae34d49fd359ce2db679eabf1ca3865eb609"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:12:01.769031Z","signature_b64":"ZJO6cRnupNP48zEudodxlQakeZIW70IVr7iRKGe5JloLLiZSOYqzTwYu4SWlgqRm2wRDen2Rn46gqOksAP/+BQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e72810dd2d993c6f2eb6c365a0e98af8f91b4fa8a8d76b9046eb39dcdfa3f7bd","last_reissued_at":"2026-05-18T01:12:01.768681Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:12:01.768681Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Unifying Framework for Adaptive Radar Detection in Homogeneous plus Structured Interference-Part II: Detectors Design","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT","stat.ME"],"primary_cat":"cs.IT","authors_text":"Antonio De Maio, Danilo Orlando, Domenico Ciuonzo","submitted_at":"2015-07-19T09:23:10Z","abstract_excerpt":"This paper deals with the problem of adaptive multidimensional/multichannel signal detection in homogeneous Gaussian disturbance with unknown covariance matrix and structured (unknown) deterministic interference. The aforementioned problem extends the well-known Generalized Multivariate Analysis of Variance (GMANOVA) tackled in the open literature. In a companion paper, we have obtained the Maximal Invariant Statistic (MIS) for the problem under consideration, as an enabling tool for the design of suitable detectors which possess the Constant False-Alarm Rate (CFAR) property. Herein, we focus "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1507.05266","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"1507.05266","created_at":"2026-05-18T01:12:01.768739+00:00"},{"alias_kind":"arxiv_version","alias_value":"1507.05266v1","created_at":"2026-05-18T01:12:01.768739+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1507.05266","created_at":"2026-05-18T01:12:01.768739+00:00"},{"alias_kind":"pith_short_12","alias_value":"44UBBXJNTE6G","created_at":"2026-05-18T12:29:02.477457+00:00"},{"alias_kind":"pith_short_16","alias_value":"44UBBXJNTE6G6LVW","created_at":"2026-05-18T12:29:02.477457+00:00"},{"alias_kind":"pith_short_8","alias_value":"44UBBXJN","created_at":"2026-05-18T12:29:02.477457+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/44UBBXJNTE6G6LVWYNS2B2MK7D","json":"https://pith.science/pith/44UBBXJNTE6G6LVWYNS2B2MK7D.json","graph_json":"https://pith.science/api/pith-number/44UBBXJNTE6G6LVWYNS2B2MK7D/graph.json","events_json":"https://pith.science/api/pith-number/44UBBXJNTE6G6LVWYNS2B2MK7D/events.json","paper":"https://pith.science/paper/44UBBXJN"},"agent_actions":{"view_html":"https://pith.science/pith/44UBBXJNTE6G6LVWYNS2B2MK7D","download_json":"https://pith.science/pith/44UBBXJNTE6G6LVWYNS2B2MK7D.json","view_paper":"https://pith.science/paper/44UBBXJN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1507.05266&json=true","fetch_graph":"https://pith.science/api/pith-number/44UBBXJNTE6G6LVWYNS2B2MK7D/graph.json","fetch_events":"https://pith.science/api/pith-number/44UBBXJNTE6G6LVWYNS2B2MK7D/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/44UBBXJNTE6G6LVWYNS2B2MK7D/action/timestamp_anchor","attest_storage":"https://pith.science/pith/44UBBXJNTE6G6LVWYNS2B2MK7D/action/storage_attestation","attest_author":"https://pith.science/pith/44UBBXJNTE6G6LVWYNS2B2MK7D/action/author_attestation","sign_citation":"https://pith.science/pith/44UBBXJNTE6G6LVWYNS2B2MK7D/action/citation_signature","submit_replication":"https://pith.science/pith/44UBBXJNTE6G6LVWYNS2B2MK7D/action/replication_record"}},"created_at":"2026-05-18T01:12:01.768739+00:00","updated_at":"2026-05-18T01:12:01.768739+00:00"}