@InProceedings{8081421,
  author = {S. Scott and J. Wawrzynek},
  booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},
  title = {Compressive sensing and sparse antenna arrays for indoor 3-D microwave imaging},
  year = {2017},
  pages = {1314-1318},
  abstract = {A new 3-D microwave imaging technique, based on compressive sensing, is proposed for use with sparse antenna arrays. It was designed to enable cost-effective 3-D imaging and tracking of people in an indoor environment. This algorithm is able to image both sparse and cluttered environments, through the use of wavelet transforms and compressive sensing techniques. The main advantage of the proposed technique is that it enables the use of much sparser antenna arrays than is possible with the traditional range-migration algorithm, reducing the cost of microwave imaging systems. Experiments show that the compressive sensing algorithm produced high quality 3-D images using antenna arrays that are 90 to 96% sparse. This reduces the cost of the antenna array by a factor of 10 to 25, when compared to traditional dense arrays, without a loss in image resolution.},
  keywords = {antenna arrays;array signal processing;compressed sensing;image resolution;indoor radio;microwave imaging;stereo image processing;sparse antenna arrays;sparse environments;cluttered environments;compressive sensing techniques;sparser antenna arrays;microwave imaging systems;compressive sensing algorithm;image resolution;high quality 3D images;indoor 3D microwave imaging;Microwave antenna arrays;Transmitting antennas;Receiving antennas;Antenna measurements;Microwave imaging;Microwave imaging;compressed sensing},
  doi = {10.23919/EUSIPCO.2017.8081421},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570342751.pdf},
}

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The main advantage of the proposed technique is that it enables the use of much sparser antenna arrays than is possible with the traditional range-migration algorithm, reducing the cost of microwave imaging systems. Experiments show that the compressive sensing algorithm produced high quality 3-D images using antenna arrays that are 90 to 96% sparse. This reduces the cost of the antenna array by a factor of 10 to 25, when compared to traditional dense arrays, without a loss in image resolution.","keywords":"antenna arrays;array signal processing;compressed sensing;image resolution;indoor radio;microwave imaging;stereo image processing;sparse antenna arrays;sparse environments;cluttered environments;compressive sensing techniques;sparser antenna arrays;microwave imaging systems;compressive sensing algorithm;image resolution;high quality 3D images;indoor 3D microwave imaging;Microwave antenna arrays;Transmitting antennas;Receiving antennas;Antenna measurements;Microwave imaging;Microwave imaging;compressed sensing","doi":"10.23919/EUSIPCO.2017.8081421","issn":"2076-1465","month":"Aug","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570342751.pdf","bibtex":"@InProceedings{8081421,\n author = {S. Scott and J. Wawrzynek},\n booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},\n title = {Compressive sensing and sparse antenna arrays for indoor 3-D microwave imaging},\n year = {2017},\n pages = {1314-1318},\n abstract = {A new 3-D microwave imaging technique, based on compressive sensing, is proposed for use with sparse antenna arrays. It was designed to enable cost-effective 3-D imaging and tracking of people in an indoor environment. This algorithm is able to image both sparse and cluttered environments, through the use of wavelet transforms and compressive sensing techniques. The main advantage of the proposed technique is that it enables the use of much sparser antenna arrays than is possible with the traditional range-migration algorithm, reducing the cost of microwave imaging systems. Experiments show that the compressive sensing algorithm produced high quality 3-D images using antenna arrays that are 90 to 96% sparse. 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