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        "author": "Tamas Peto",
        "author_email": "petotax@gmail.com",
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        "description": "# pyArgus\n\nThis python package aims to implement signal processing algorithms applicable in antenna arrays. The implementation mainly focuses on the beamforming and\ndirection finding algorithms.\nFor array synthesis and radiation pattern optimization please check the \"arraytool\" python package.\nhttps://github.com/zinka/arraytool and https://zinka.wordpress.com/ by S. R. Zinka\n\nNamed after Argus the giant from the greek mitology who had hundreds of eyes.\n\n### Package organization:\n\n- pyArgus: Main package\n\t- antennaArrayPattern: Implements the radiation pattern calculation of antenna arrays\n\t- beamform: Implements beamformer algorithms.\n\t- directionEstimation: Implements DOA estimation algorithms and method for estimating the spatial correlation matrix.\n- test: Sub package\n\tcontains demonstration functions for antenna pattern plot, beamforming and direction of arrival estimation. \n\n### Implemented Algorithms\n\n- Beamforiming:\n    - Fixed beamformers:\n        - Maximum Signal to Interference Ratio beamformer\n        - Maximum Signal to Interference Ratio beamformer with Godara's method\n    - Adaptive beamformer:\n        - Optimum Wiener beamformer (with known signal of interest direction)\n        - MSINR with known covariance matrices\n        - MMSE with known signal of interest\n\n- Direction of Arrival Estimation:\n    - DOA algorithms:\n        - Bartlett (Fourier) method\n        - Capon's method\n        - Burg's Maximum Entropy Method (MEM)\n        - Multiple Signal Classification (MUSIC)\n        - Multi Dimension MUSIC (MD-MUSIC)\n\n    - Util functions:\n        - Spatial correlation matrix estimation using the sample average technique\n        - Forward-backward averaging\n        - Spatial smoothing\n        - DOA results plot with highlighting the ambiguous regions (Only for Uniform linear arrays)\n\n### Antenna Array Pattern Plot Features\n- Arbitrary configured planar antenna systems\n- Takes into account the pattern of the signal radiating elements\n\nThe documentation of the package is written in Jupyter notebook, which can be found on the following sites:\n\nGithub: [github.com/petotamas/pyArgus](https://github.com/petotamas/pyArgus)\n\nPersonal website: [tamaspeto.com](https://www.tamaspeto.com/pyargus) \n\nTam\u00e1s Pet\u0151 2016-2019, Hungary\n\n\n\n\n",
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