{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2016:PR7E4EG6DAEPB72Y7SSGMK3TKC","short_pith_number":"pith:PR7E4EG6","canonical_record":{"source":{"id":"1602.05540","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-02-15T21:38:48Z","cross_cats_sorted":[],"title_canon_sha256":"4bf660fd5bfcda616c8c553a981c136d37b4cd6505ebd69cce1bd3f6216b1a8c","abstract_canon_sha256":"e0bd642c6e81c585ee10e33430a78d97b930b47d74d7df6eda0952a15f5c463c"},"schema_version":"1.0"},"canonical_sha256":"7c7e4e10de1808f0ff58fca4662b73508708a1f29b55888bf74e20429d6a9d1c","source":{"kind":"arxiv","id":"1602.05540","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.05540","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"arxiv_version","alias_value":"1602.05540v1","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.05540","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"pith_short_12","alias_value":"PR7E4EG6DAEP","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_16","alias_value":"PR7E4EG6DAEPB72Y","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_8","alias_value":"PR7E4EG6","created_at":"2026-05-18T12:30:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2016:PR7E4EG6DAEPB72Y7SSGMK3TKC","target":"record","payload":{"canonical_record":{"source":{"id":"1602.05540","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-02-15T21:38:48Z","cross_cats_sorted":[],"title_canon_sha256":"4bf660fd5bfcda616c8c553a981c136d37b4cd6505ebd69cce1bd3f6216b1a8c","abstract_canon_sha256":"e0bd642c6e81c585ee10e33430a78d97b930b47d74d7df6eda0952a15f5c463c"},"schema_version":"1.0"},"canonical_sha256":"7c7e4e10de1808f0ff58fca4662b73508708a1f29b55888bf74e20429d6a9d1c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:20:26.931056Z","signature_b64":"R4pWVl3KIFMv/E+nSBV1bHpIx+tVG4lbKti0h6DeJLRcrZCdNDyZf5dcmJtmJlHQy1GGrU6p5mhNM7lfCLcXBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7c7e4e10de1808f0ff58fca4662b73508708a1f29b55888bf74e20429d6a9d1c","last_reissued_at":"2026-05-18T01:20:26.930493Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:20:26.930493Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1602.05540","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:20:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yXqm65Q7NibWIAlJj1hvficMvUcgYRqqSk8yYNzFL6ztQTsrvFZLOF/qV3Rg4jPI4Md8w85DwidngRXfSB3xCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T21:52:21.300953Z"},"content_sha256":"87a2fa5b67abbda78f994e095203a7f960536e67c20d2f82f69189dae7b8cee3","schema_version":"1.0","event_id":"sha256:87a2fa5b67abbda78f994e095203a7f960536e67c20d2f82f69189dae7b8cee3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2016:PR7E4EG6DAEPB72Y7SSGMK3TKC","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Robust Covariance Estimation under Imperfect Constraints using an Expected Likelihood Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"stat.ME","authors_text":"Bosung Kang, Muralidhar Rangaswamy, Vishal Monga, Yuri I. Abramovich","submitted_at":"2016-02-15T21:38:48Z","abstract_excerpt":"We address the problem of structured covariance matrix estimation for radar space-time adaptive processing (STAP). A priori knowledge of the interference environment has been exploited in many previous works to enable accurate estimators even when training is not generous. Specifically, recent work has shown that employing practical constraints such as the rank of clutter subspace and the condition number of disturbance covariance leads to powerful estimators that have closed form solutions. While rank and the condition number are very effective constraints, often practical non-idealities make"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.05540","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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-18T01:20:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1bSczS/bFZvhq0FXP3htKv620w3aFl9UUZBT22cRiKbWcir4A23fr5bbPlRfakBX0x31Ss8SvwdTX7cTiLrJDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-22T21:52:21.301291Z"},"content_sha256":"539509743edab2d4a9b7a276023ae3c26fd48d319bd227701bf767fcfe3536c2","schema_version":"1.0","event_id":"sha256:539509743edab2d4a9b7a276023ae3c26fd48d319bd227701bf767fcfe3536c2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/PR7E4EG6DAEPB72Y7SSGMK3TKC/bundle.json","state_url":"https://pith.science/pith/PR7E4EG6DAEPB72Y7SSGMK3TKC/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/PR7E4EG6DAEPB72Y7SSGMK3TKC/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-06-22T21:52:21Z","links":{"resolver":"https://pith.science/pith/PR7E4EG6DAEPB72Y7SSGMK3TKC","bundle":"https://pith.science/pith/PR7E4EG6DAEPB72Y7SSGMK3TKC/bundle.json","state":"https://pith.science/pith/PR7E4EG6DAEPB72Y7SSGMK3TKC/state.json","well_known_bundle":"https://pith.science/.well-known/pith/PR7E4EG6DAEPB72Y7SSGMK3TKC/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2016:PR7E4EG6DAEPB72Y7SSGMK3TKC","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"e0bd642c6e81c585ee10e33430a78d97b930b47d74d7df6eda0952a15f5c463c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-02-15T21:38:48Z","title_canon_sha256":"4bf660fd5bfcda616c8c553a981c136d37b4cd6505ebd69cce1bd3f6216b1a8c"},"schema_version":"1.0","source":{"id":"1602.05540","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1602.05540","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"arxiv_version","alias_value":"1602.05540v1","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1602.05540","created_at":"2026-05-18T01:20:26Z"},{"alias_kind":"pith_short_12","alias_value":"PR7E4EG6DAEP","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_16","alias_value":"PR7E4EG6DAEPB72Y","created_at":"2026-05-18T12:30:39Z"},{"alias_kind":"pith_short_8","alias_value":"PR7E4EG6","created_at":"2026-05-18T12:30:39Z"}],"graph_snapshots":[{"event_id":"sha256:539509743edab2d4a9b7a276023ae3c26fd48d319bd227701bf767fcfe3536c2","target":"graph","created_at":"2026-05-18T01:20:26Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"paper":{"abstract_excerpt":"We address the problem of structured covariance matrix estimation for radar space-time adaptive processing (STAP). A priori knowledge of the interference environment has been exploited in many previous works to enable accurate estimators even when training is not generous. Specifically, recent work has shown that employing practical constraints such as the rank of clutter subspace and the condition number of disturbance covariance leads to powerful estimators that have closed form solutions. While rank and the condition number are very effective constraints, often practical non-idealities make","authors_text":"Bosung Kang, Muralidhar Rangaswamy, Vishal Monga, Yuri I. Abramovich","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-02-15T21:38:48Z","title":"Robust Covariance Estimation under Imperfect Constraints using an Expected Likelihood Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1602.05540","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:87a2fa5b67abbda78f994e095203a7f960536e67c20d2f82f69189dae7b8cee3","target":"record","created_at":"2026-05-18T01:20:26Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"e0bd642c6e81c585ee10e33430a78d97b930b47d74d7df6eda0952a15f5c463c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"stat.ME","submitted_at":"2016-02-15T21:38:48Z","title_canon_sha256":"4bf660fd5bfcda616c8c553a981c136d37b4cd6505ebd69cce1bd3f6216b1a8c"},"schema_version":"1.0","source":{"id":"1602.05540","kind":"arxiv","version":1}},"canonical_sha256":"7c7e4e10de1808f0ff58fca4662b73508708a1f29b55888bf74e20429d6a9d1c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7c7e4e10de1808f0ff58fca4662b73508708a1f29b55888bf74e20429d6a9d1c","first_computed_at":"2026-05-18T01:20:26.930493Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T01:20:26.930493Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"R4pWVl3KIFMv/E+nSBV1bHpIx+tVG4lbKti0h6DeJLRcrZCdNDyZf5dcmJtmJlHQy1GGrU6p5mhNM7lfCLcXBg==","signature_status":"signed_v1","signed_at":"2026-05-18T01:20:26.931056Z","signed_message":"canonical_sha256_bytes"},"source_id":"1602.05540","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:87a2fa5b67abbda78f994e095203a7f960536e67c20d2f82f69189dae7b8cee3","sha256:539509743edab2d4a9b7a276023ae3c26fd48d319bd227701bf767fcfe3536c2"],"state_sha256":"c19e9757cd2366969c28c32fc52bf48d789bfd9460377ff0e6569fdc2176f9b6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Q08SmZvVnmmQqAd1g91UzVlZSvidnqwUVzY7g7gig6xYET1Zg3JlYG3mJ62Sh7Zu+7HzssIa2sEeenGfdFljCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-22T21:52:21.303212Z","bundle_sha256":"804f60625d9d7d8232a15592371d711dad89b8dbf9b0452bfe3d4527eea92f24"}}