A Robust DOA Estimator Based on Compressive Sensing for Coprime Array in the Presence of Miscalibrated Sensors
Coprime array with <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mo>+</mo> <mi>N</mi> </mrow> </semantics> </math> </inline-formula> sensors can achieve an increased degrees-of-fre...
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MDPI AG
2019-08-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/19/16/3538 |
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| author | Jiaxun Kou Ming Li Chunlan Jiang |
| author_facet | Jiaxun Kou Ming Li Chunlan Jiang |
| author_sort | Jiaxun Kou |
| collection | DOAJ |
| description | Coprime array with <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mo>+</mo> <mi>N</mi> </mrow> </semantics> </math> </inline-formula> sensors can achieve an increased degrees-of-freedom (DOF) of <inline-formula> <math display="inline"> <semantics> <mrow> <mi mathvariant="script">O</mi> <mrow> <mo>(</mo> <mrow> <mi>M</mi> <mi>N</mi> </mrow> <mo>)</mo> </mrow> </mrow> </semantics> </math> </inline-formula> for direction-of-arrival (DOA) estimation. Utilizing the compressive sensing (CS)-based DOA estimation methods, the increased DOF offered by the coprime array can be fully exploited. However, when some sensors in the array are miscalibrated, these DOA estimation methods suffer from degraded performance or even failed operation. Besides, the key to the success of CS-based DOA estimation is that every target falls on the predefined grid. Thus, a coarse grid may cause the mismatch problem, whereas a fine grid requires great computational cost. In this paper, a robust CS-based DOA estimation algorithm is proposed for coprime array with miscalibrated sensors. In the proposed algorithm, signals received by the miscalibrated sensors are viewed as outliers, and correntropy is introduced as the similarity measurement to distinguish these outliers. Incorporated with maximum correntropy criterion (MCC), an iterative sparse reconstruction-based algorithm is then developed to give the DOA estimation while mitigating the influence of the outliers. A multiresolution grid refinement strategy is also incorporated to reconcile the contradiction between computational cost and the mismatch problem. The numerical simulation results verify the effectiveness and robustness of the proposed method. |
| first_indexed | 2024-04-13T00:45:45Z |
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| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T00:45:45Z |
| publishDate | 2019-08-01 |
| publisher | MDPI AG |
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| series | Sensors |
| spelling | doaj.art-af7b64e8cbee4dbbaffce2e93f16a0f12022-12-22T03:10:02ZengMDPI AGSensors1424-82202019-08-011916353810.3390/s19163538s19163538A Robust DOA Estimator Based on Compressive Sensing for Coprime Array in the Presence of Miscalibrated SensorsJiaxun Kou0Ming Li1Chunlan Jiang2State Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, ChinaState Key Laboratory of Explosion Science and Technology, Beijing Institute of Technology, Beijing 100081, ChinaCoprime array with <inline-formula> <math display="inline"> <semantics> <mrow> <mi>M</mi> <mo>+</mo> <mi>N</mi> </mrow> </semantics> </math> </inline-formula> sensors can achieve an increased degrees-of-freedom (DOF) of <inline-formula> <math display="inline"> <semantics> <mrow> <mi mathvariant="script">O</mi> <mrow> <mo>(</mo> <mrow> <mi>M</mi> <mi>N</mi> </mrow> <mo>)</mo> </mrow> </mrow> </semantics> </math> </inline-formula> for direction-of-arrival (DOA) estimation. Utilizing the compressive sensing (CS)-based DOA estimation methods, the increased DOF offered by the coprime array can be fully exploited. However, when some sensors in the array are miscalibrated, these DOA estimation methods suffer from degraded performance or even failed operation. Besides, the key to the success of CS-based DOA estimation is that every target falls on the predefined grid. Thus, a coarse grid may cause the mismatch problem, whereas a fine grid requires great computational cost. In this paper, a robust CS-based DOA estimation algorithm is proposed for coprime array with miscalibrated sensors. In the proposed algorithm, signals received by the miscalibrated sensors are viewed as outliers, and correntropy is introduced as the similarity measurement to distinguish these outliers. Incorporated with maximum correntropy criterion (MCC), an iterative sparse reconstruction-based algorithm is then developed to give the DOA estimation while mitigating the influence of the outliers. A multiresolution grid refinement strategy is also incorporated to reconcile the contradiction between computational cost and the mismatch problem. The numerical simulation results verify the effectiveness and robustness of the proposed method.https://www.mdpi.com/1424-8220/19/16/3538robust direction-of-arrival (DOA)coprime arraycompressive sensing (CS)calibration erroroutliermaximum correntropy criterion (MCC) |
| spellingShingle | Jiaxun Kou Ming Li Chunlan Jiang A Robust DOA Estimator Based on Compressive Sensing for Coprime Array in the Presence of Miscalibrated Sensors Sensors robust direction-of-arrival (DOA) coprime array compressive sensing (CS) calibration error outlier maximum correntropy criterion (MCC) |
| title | A Robust DOA Estimator Based on Compressive Sensing for Coprime Array in the Presence of Miscalibrated Sensors |
| title_full | A Robust DOA Estimator Based on Compressive Sensing for Coprime Array in the Presence of Miscalibrated Sensors |
| title_fullStr | A Robust DOA Estimator Based on Compressive Sensing for Coprime Array in the Presence of Miscalibrated Sensors |
| title_full_unstemmed | A Robust DOA Estimator Based on Compressive Sensing for Coprime Array in the Presence of Miscalibrated Sensors |
| title_short | A Robust DOA Estimator Based on Compressive Sensing for Coprime Array in the Presence of Miscalibrated Sensors |
| title_sort | robust doa estimator based on compressive sensing for coprime array in the presence of miscalibrated sensors |
| topic | robust direction-of-arrival (DOA) coprime array compressive sensing (CS) calibration error outlier maximum correntropy criterion (MCC) |
| url | https://www.mdpi.com/1424-8220/19/16/3538 |
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