Optimization of Radar Parameters for Maximum Detection Probability Under Generalized Discrete Clutter Conditions Using Stochastic Geometry
We propose an analytical framework based on stochastic geometry (SG) formulations to estimate a radar's detection performance under generalized discrete clutter conditions. We model the spatial distribution of discrete clutter scatterers as a homogeneous Poisson point process and the rada...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Open Journal of Signal Processing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9580712/ |
| _version_ | 1818871169678311424 |
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| author | Shobha Sundar Ram Gaurav Singh Gourab Ghatak |
| author_facet | Shobha Sundar Ram Gaurav Singh Gourab Ghatak |
| author_sort | Shobha Sundar Ram |
| collection | DOAJ |
| description | We propose an analytical framework based on stochastic geometry (SG) formulations to estimate a radar's detection performance under generalized discrete clutter conditions. We model the spatial distribution of discrete clutter scatterers as a homogeneous Poisson point process and the radar cross-section of each extended scatterer as a random variable of the Weibull distribution. Using this framework, we derive a metric called the radar detection coverage probability as a function of radar parameters such as transmitted power, system noise temperature and radar bandwidth; and clutter parameters such as clutter density and mean clutter cross-section. We derive the optimum radar bandwidth for maximizing this metric under noisy and cluttered conditions. We also derive the peak transmitted power beyond which there will be no discernible improvement in radar detection performance due to clutter limited conditions. When both transmitted power and bandwidth are fixed, we show how the detection threshold can be optimized for best performance. We experimentally validate the SG results with a hybrid of Monte Carlo and full wave electromagnetic solver based simulations using finite difference time domain (FDTD) techniques. |
| first_indexed | 2024-12-19T12:18:39Z |
| format | Article |
| id | doaj.art-366a8b58b3a4429493019bc65592ccde |
| institution | Directory Open Access Journal |
| issn | 2644-1322 |
| language | English |
| last_indexed | 2024-12-19T12:18:39Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Signal Processing |
| spelling | doaj.art-366a8b58b3a4429493019bc65592ccde2022-12-21T20:21:53ZengIEEEIEEE Open Journal of Signal Processing2644-13222021-01-01257158510.1109/OJSP.2021.31211999580712Optimization of Radar Parameters for Maximum Detection Probability Under Generalized Discrete Clutter Conditions Using Stochastic GeometryShobha Sundar Ram0https://orcid.org/0000-0002-0265-8610Gaurav Singh1Gourab Ghatak2https://orcid.org/0000-0002-8240-4038Indraprastha Institute of Information Technology Delhi, New Delhi, IndiaIndraprastha Institute of Information Technology Delhi, New Delhi, IndiaIndraprastha Institute of Information Technology Delhi, New Delhi, IndiaWe propose an analytical framework based on stochastic geometry (SG) formulations to estimate a radar's detection performance under generalized discrete clutter conditions. We model the spatial distribution of discrete clutter scatterers as a homogeneous Poisson point process and the radar cross-section of each extended scatterer as a random variable of the Weibull distribution. Using this framework, we derive a metric called the radar detection coverage probability as a function of radar parameters such as transmitted power, system noise temperature and radar bandwidth; and clutter parameters such as clutter density and mean clutter cross-section. We derive the optimum radar bandwidth for maximizing this metric under noisy and cluttered conditions. We also derive the peak transmitted power beyond which there will be no discernible improvement in radar detection performance due to clutter limited conditions. When both transmitted power and bandwidth are fixed, we show how the detection threshold can be optimized for best performance. We experimentally validate the SG results with a hybrid of Monte Carlo and full wave electromagnetic solver based simulations using finite difference time domain (FDTD) techniques.https://ieeexplore.ieee.org/document/9580712/Stochastic geometryradar detectionFDTDMonte Carlo simulationsindoor clutterPoisson point process |
| spellingShingle | Shobha Sundar Ram Gaurav Singh Gourab Ghatak Optimization of Radar Parameters for Maximum Detection Probability Under Generalized Discrete Clutter Conditions Using Stochastic Geometry IEEE Open Journal of Signal Processing Stochastic geometry radar detection FDTD Monte Carlo simulations indoor clutter Poisson point process |
| title | Optimization of Radar Parameters for Maximum Detection Probability Under Generalized Discrete Clutter Conditions Using Stochastic Geometry |
| title_full | Optimization of Radar Parameters for Maximum Detection Probability Under Generalized Discrete Clutter Conditions Using Stochastic Geometry |
| title_fullStr | Optimization of Radar Parameters for Maximum Detection Probability Under Generalized Discrete Clutter Conditions Using Stochastic Geometry |
| title_full_unstemmed | Optimization of Radar Parameters for Maximum Detection Probability Under Generalized Discrete Clutter Conditions Using Stochastic Geometry |
| title_short | Optimization of Radar Parameters for Maximum Detection Probability Under Generalized Discrete Clutter Conditions Using Stochastic Geometry |
| title_sort | optimization of radar parameters for maximum detection probability under generalized discrete clutter conditions using stochastic geometry |
| topic | Stochastic geometry radar detection FDTD Monte Carlo simulations indoor clutter Poisson point process |
| url | https://ieeexplore.ieee.org/document/9580712/ |
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