{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2022:6SNB7QRNAG7ZKRKWQF3NQ4IR5G","short_pith_number":"pith:6SNB7QRN","schema_version":"1.0","canonical_sha256":"f49a1fc22d01bf9545568176d87111e9ae5710fcaf2a58be1f1fed838e729e31","source":{"kind":"arxiv","id":"2211.09332","version":1},"attestation_state":"computed","paper":{"title":"iNavFIter-M: Matrix Formulation of Functional Iteration for Inertial Navigation Computation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO","cs.SY"],"primary_cat":"eess.SY","authors_text":"Hongyan Jiang, Maoran Zhu, Yanyan Fu, Yuanxin Wu","submitted_at":"2022-11-17T04:39:23Z","abstract_excerpt":"The acquisition of attitude, velocity, and position is an essential task in the field of inertial navigation, achieved by integrating the measurements from inertial sensors. Recently, the ultra-precision inertial navigation computation has been tackled by the functional iteration approach (iNavFIter) that drives the non-commutativity errors almost to the computer truncation error level. This paper proposes a computationally efficient matrix formulation of the functional iteration approach, named the iNavFIter-M. The Chebyshev polynomial coefficients in two consecutive iterations are explicitly"},"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":"2211.09332","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2022-11-17T04:39:23Z","cross_cats_sorted":["cs.RO","cs.SY"],"title_canon_sha256":"e8fa084536f65867feda67446bbfd8fe927000f1a73ea4869af72feb8aadbf10","abstract_canon_sha256":"0d0ddb43e77cd1cdb5d85d20f21f1560f68325a2edb30d2f112c9c0154b66ae3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:16:54.666743Z","signature_b64":"V6gjdBXZL0E5qWrPI6xChfniXtKZgKilnm4sA/OTKy0hnswFiQq9Lam6m/ZubaMskvEZCBjvwrdFr7mXIF48Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f49a1fc22d01bf9545568176d87111e9ae5710fcaf2a58be1f1fed838e729e31","last_reissued_at":"2026-07-05T05:16:54.666401Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:16:54.666401Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"iNavFIter-M: Matrix Formulation of Functional Iteration for Inertial Navigation Computation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO","cs.SY"],"primary_cat":"eess.SY","authors_text":"Hongyan Jiang, Maoran Zhu, Yanyan Fu, Yuanxin Wu","submitted_at":"2022-11-17T04:39:23Z","abstract_excerpt":"The acquisition of attitude, velocity, and position is an essential task in the field of inertial navigation, achieved by integrating the measurements from inertial sensors. Recently, the ultra-precision inertial navigation computation has been tackled by the functional iteration approach (iNavFIter) that drives the non-commutativity errors almost to the computer truncation error level. This paper proposes a computationally efficient matrix formulation of the functional iteration approach, named the iNavFIter-M. The Chebyshev polynomial coefficients in two consecutive iterations are explicitly"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.09332","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2211.09332/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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":"2211.09332","created_at":"2026-07-05T05:16:54.666459+00:00"},{"alias_kind":"arxiv_version","alias_value":"2211.09332v1","created_at":"2026-07-05T05:16:54.666459+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.09332","created_at":"2026-07-05T05:16:54.666459+00:00"},{"alias_kind":"pith_short_12","alias_value":"6SNB7QRNAG7Z","created_at":"2026-07-05T05:16:54.666459+00:00"},{"alias_kind":"pith_short_16","alias_value":"6SNB7QRNAG7ZKRKW","created_at":"2026-07-05T05:16:54.666459+00:00"},{"alias_kind":"pith_short_8","alias_value":"6SNB7QRN","created_at":"2026-07-05T05:16:54.666459+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/6SNB7QRNAG7ZKRKWQF3NQ4IR5G","json":"https://pith.science/pith/6SNB7QRNAG7ZKRKWQF3NQ4IR5G.json","graph_json":"https://pith.science/api/pith-number/6SNB7QRNAG7ZKRKWQF3NQ4IR5G/graph.json","events_json":"https://pith.science/api/pith-number/6SNB7QRNAG7ZKRKWQF3NQ4IR5G/events.json","paper":"https://pith.science/paper/6SNB7QRN"},"agent_actions":{"view_html":"https://pith.science/pith/6SNB7QRNAG7ZKRKWQF3NQ4IR5G","download_json":"https://pith.science/pith/6SNB7QRNAG7ZKRKWQF3NQ4IR5G.json","view_paper":"https://pith.science/paper/6SNB7QRN","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2211.09332&json=true","fetch_graph":"https://pith.science/api/pith-number/6SNB7QRNAG7ZKRKWQF3NQ4IR5G/graph.json","fetch_events":"https://pith.science/api/pith-number/6SNB7QRNAG7ZKRKWQF3NQ4IR5G/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/6SNB7QRNAG7ZKRKWQF3NQ4IR5G/action/timestamp_anchor","attest_storage":"https://pith.science/pith/6SNB7QRNAG7ZKRKWQF3NQ4IR5G/action/storage_attestation","attest_author":"https://pith.science/pith/6SNB7QRNAG7ZKRKWQF3NQ4IR5G/action/author_attestation","sign_citation":"https://pith.science/pith/6SNB7QRNAG7ZKRKWQF3NQ4IR5G/action/citation_signature","submit_replication":"https://pith.science/pith/6SNB7QRNAG7ZKRKWQF3NQ4IR5G/action/replication_record"}},"created_at":"2026-07-05T05:16:54.666459+00:00","updated_at":"2026-07-05T05:16:54.666459+00:00"}