{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:G5YCXPIA6CU3Q57CD6ZNY2DSIG","short_pith_number":"pith:G5YCXPIA","schema_version":"1.0","canonical_sha256":"37702bbd00f0a9b877e21fb2dc6872418be4512428be3211addb6cc80c8c2dbe","source":{"kind":"arxiv","id":"2304.07596","version":1},"attestation_state":"computed","paper":{"title":"Acoustic Beamforming for Object-relative Distance Estimation and Control in Unmanned Air Vehicles using Propulsion System Noise","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SD","eess.AS"],"primary_cat":"cs.RO","authors_text":"Alisha Sharma, Daniel Lofaro, Donald Sofge, Jason Geder, Joseph Lingevitch, Theodore Martin","submitted_at":"2023-04-15T17:03:21Z","abstract_excerpt":"Unmanned air vehicles often produce significant noise from their propulsion systems. Using this broadband signal as \"acoustic illumination\" for an auxiliary sensing system could make vehicles more robust at a minimal cost. We present an acoustic beamforming-based algorithm that estimates object-relative distance with a small two-microphone array using the generated propulsion system noise of a vehicle. We demonstrate this approach in several closed-loop distance feedback control tests with a mounted quad-rotor vehicle in a noisy environment and show accurate object-relative distance estimates "},"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":"2304.07596","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.RO","submitted_at":"2023-04-15T17:03:21Z","cross_cats_sorted":["cs.SD","eess.AS"],"title_canon_sha256":"8990d65df9aa9a806e2bbb747c92d90b88c2439967694f2fe68612dba5e72c81","abstract_canon_sha256":"237bb777c2ec96db6e8bb61310649f2cf8d9ad9910ebd0960f6a264579853166"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:01:38.347543Z","signature_b64":"VtuU3yjyxfJupwfiF50hK2gcqDGetPwL1wXTT9A1AtjOWUCoHkBIj/PZumeO6A5f0Rwm5KP7ypuDeRsORrePAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"37702bbd00f0a9b877e21fb2dc6872418be4512428be3211addb6cc80c8c2dbe","last_reissued_at":"2026-07-05T06:01:38.347112Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:01:38.347112Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Acoustic Beamforming for Object-relative Distance Estimation and Control in Unmanned Air Vehicles using Propulsion System Noise","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SD","eess.AS"],"primary_cat":"cs.RO","authors_text":"Alisha Sharma, Daniel Lofaro, Donald Sofge, Jason Geder, Joseph Lingevitch, Theodore Martin","submitted_at":"2023-04-15T17:03:21Z","abstract_excerpt":"Unmanned air vehicles often produce significant noise from their propulsion systems. Using this broadband signal as \"acoustic illumination\" for an auxiliary sensing system could make vehicles more robust at a minimal cost. We present an acoustic beamforming-based algorithm that estimates object-relative distance with a small two-microphone array using the generated propulsion system noise of a vehicle. We demonstrate this approach in several closed-loop distance feedback control tests with a mounted quad-rotor vehicle in a noisy environment and show accurate object-relative distance estimates "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.07596","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/2304.07596/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":"2304.07596","created_at":"2026-07-05T06:01:38.347168+00:00"},{"alias_kind":"arxiv_version","alias_value":"2304.07596v1","created_at":"2026-07-05T06:01:38.347168+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.07596","created_at":"2026-07-05T06:01:38.347168+00:00"},{"alias_kind":"pith_short_12","alias_value":"G5YCXPIA6CU3","created_at":"2026-07-05T06:01:38.347168+00:00"},{"alias_kind":"pith_short_16","alias_value":"G5YCXPIA6CU3Q57C","created_at":"2026-07-05T06:01:38.347168+00:00"},{"alias_kind":"pith_short_8","alias_value":"G5YCXPIA","created_at":"2026-07-05T06:01:38.347168+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2507.05584","citing_title":"The Fourier Spectral Transformer Networks For Efficient and Generalizable Nonlinear PDEs Prediction","ref_index":18,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/G5YCXPIA6CU3Q57CD6ZNY2DSIG","json":"https://pith.science/pith/G5YCXPIA6CU3Q57CD6ZNY2DSIG.json","graph_json":"https://pith.science/api/pith-number/G5YCXPIA6CU3Q57CD6ZNY2DSIG/graph.json","events_json":"https://pith.science/api/pith-number/G5YCXPIA6CU3Q57CD6ZNY2DSIG/events.json","paper":"https://pith.science/paper/G5YCXPIA"},"agent_actions":{"view_html":"https://pith.science/pith/G5YCXPIA6CU3Q57CD6ZNY2DSIG","download_json":"https://pith.science/pith/G5YCXPIA6CU3Q57CD6ZNY2DSIG.json","view_paper":"https://pith.science/paper/G5YCXPIA","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2304.07596&json=true","fetch_graph":"https://pith.science/api/pith-number/G5YCXPIA6CU3Q57CD6ZNY2DSIG/graph.json","fetch_events":"https://pith.science/api/pith-number/G5YCXPIA6CU3Q57CD6ZNY2DSIG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/G5YCXPIA6CU3Q57CD6ZNY2DSIG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/G5YCXPIA6CU3Q57CD6ZNY2DSIG/action/storage_attestation","attest_author":"https://pith.science/pith/G5YCXPIA6CU3Q57CD6ZNY2DSIG/action/author_attestation","sign_citation":"https://pith.science/pith/G5YCXPIA6CU3Q57CD6ZNY2DSIG/action/citation_signature","submit_replication":"https://pith.science/pith/G5YCXPIA6CU3Q57CD6ZNY2DSIG/action/replication_record"}},"created_at":"2026-07-05T06:01:38.347168+00:00","updated_at":"2026-07-05T06:01:38.347168+00:00"}