{"id":37074991,"url":"https://github.com/zhiim/doa_py","last_synced_at":"2026-01-14T08:50:14.293Z","repository":{"id":217692013,"uuid":"719942080","full_name":"zhiim/doa_py","owner":"zhiim","description":"DOA etimation algorithms implemented in Python for ULA, UCA and broadband/wideband DOA estimation","archived":false,"fork":false,"pushed_at":"2025-11-25T13:37:04.000Z","size":4004,"stargazers_count":41,"open_issues_count":1,"forks_count":4,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-11-27T12:50:55.599Z","etag":null,"topics":["aoa","array","array-signal-processing","direction-of-arrival","doa","doa-estimation","signal-processing"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/zhiim.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-11-17T08:29:51.000Z","updated_at":"2025-11-25T13:37:07.000Z","dependencies_parsed_at":"2024-02-08T06:22:13.912Z","dependency_job_id":"9859dbf5-8aaa-43fd-bd20-205371d6d711","html_url":"https://github.com/zhiim/doa_py","commit_stats":null,"previous_names":["zhiim/classical_doa"],"tags_count":12,"template":false,"template_full_name":null,"purl":"pkg:github/zhiim/doa_py","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zhiim%2Fdoa_py","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zhiim%2Fdoa_py/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zhiim%2Fdoa_py/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zhiim%2Fdoa_py/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/zhiim","download_url":"https://codeload.github.com/zhiim/doa_py/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zhiim%2Fdoa_py/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28414693,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-14T08:38:59.149Z","status":"ssl_error","status_checked_at":"2026-01-14T08:38:43.588Z","response_time":107,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["aoa","array","array-signal-processing","direction-of-arrival","doa","doa-estimation","signal-processing"],"created_at":"2026-01-14T08:50:13.639Z","updated_at":"2026-01-14T08:50:14.279Z","avatar_url":"https://github.com/zhiim.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n  \u003cimg src=\"pics/doa_py.svg\" alt=\"DOA_Py logo\" width=\"50%\"\u003e\n\u003c/div\u003e\n\n# DOA_Py\n\nDOA Estimation algorithms implemented in Python. It can be used for ULA, UCA and broadband/wideband DOA estimation.\n\n## Getting Started\n\n### Installation\n\n```bash\npip install doa_py\n```\n\nor install from source\n\n```bash\ngit clone https://github.com/zhiim/doa_py.git\ncd doa_py\npip install .\n```\n\n### Usage\n\nA sample example of DOA estimation using MUSIC algorithm.\n\n```python\nimport numpy as np\n\nfrom doa_py import arrays, signals\nfrom doa_py.algorithm import music\nfrom doa_py.plot import plot_spatial_spectrum\n\n# Create a 8-element ULA with 0.5m spacing\nula = arrays.UniformLinearArray(m=8, dd=0.5)\n# Create a complex stochastic signal\nsource = signals.ComplexStochasticSignal(fc=3e8)\n\n# Simulate the received data\nreceived_data = ula.received_signal(\n    signal=source, snr=0, nsamples=1000, angle_incidence=np.array([0, 30]), unit=\"deg\"\n)\n\n# Calculate the MUSIC spectrum\nangle_grids = np.arange(-90, 90, 1)\nspectrum = music(\n    received_data=received_data,\n    num_signal=2,\n    array=ula,\n    signal_fre=3e8,\n    angle_grids=angle_grids,\n    unit=\"deg\",\n)\n\n# Plot the spatial spectrum\nplot_spatial_spectrum(\n    spectrum=spectrum,\n    ground_truth=np.array([0, 30]),\n    angle_grids=angle_grids,\n    num_signal=2,\n)\n```\n\nYou will a get a figure like this:\n![music_spectrum](./pics/music_spectrum.svg)\n\nCheck [examples](./examples/) for for more details on how to use it.\n\nYou can see more plot results of the algorithm in the [Showcase](#showcase).\n\n## What's implemented\n\n### Array Structures\n\n- Uniform Linear Array (support array position error and mutual coupling error)\n- Uniform Circular Array\n\n### Signal Models\n\n- **Narrowband**\n  - _ComplexStochasticSignal_: The amplitude of signals at each sampling point is a complex random variable.\n  - _RandomFreqSignal_: Signals transmitted by different sources have different intermediate frequencies (support coherent mode).\n- **Broadband**\n  - _ChirpSignal_: Chirp signals with different chirp bandwidths within the sampling period.\n  - _MultiFreqSignal_: Broadband signals formed by the superposition of multiple single-frequency signals within a certain frequency band.\n  - _MixedSignal_: Narrorband and broadband mixed signal\n\n### Algorithms\n\n- DOA estimation for ULA\n  - [x] MUSIC\n  - [x] ESPRIT\n  - [x] Root-MUSIC\n  - [x] OMP\n  - [x] $l_1$-SVD\n- DOA estimation for URA\n  - [ ] URA-MUSIC\n  - [ ] URA-ESPRIT\n- DOA estimation for UCA\n  - [x] UCA-RB-MUSIC\n  - [x] UCA-ESPRIT\n- Broadband/Wideband DOA estimation\n  - [x] iMUSIC\n  - [x] CSSM\n  - [x] TOPS\n- Coherent DOA estimation\n  - [x] smoothed-MUSIC\n\n### Showcase\n\n![ESPRIT](./pics/esprit.svg)\n\n![$l_1$-SVD](./pics/l1_svd.svg)\n\n![UCA-RB-MUSIC](./pics/uca_rb_music.svg)\n\n## License\n\nThis project is licensed under the [MIT](LICENSE) License - see the LICENSE file for details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzhiim%2Fdoa_py","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzhiim%2Fdoa_py","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzhiim%2Fdoa_py/lists"}