### Abstract

The performance of the MUSIC estimator for the powers of uncorrelated sources arriving at a linear array is studied and is compared with the Cramer-Rao bound on the direction estimates of two closely spaced sources investigated in (Swingler, 1993). In general, it is found that if the source directions can be accurately estimated as when the sources are well separated, the estimator will function well and has a percentage variance which depends solely on the number of data samples. However, when the source separation is small and the direction estimates are poor, the normalized standard deviations of the power estimates will increase drastically and may become larger than that of the direction estimates.

Original language | English (US) |
---|---|

Pages (from-to) | 243-248 |

Number of pages | 6 |

Journal | Signal Processing |

Volume | 46 |

Issue number | 2 |

DOIs | |

State | Published - 1995 |

Externally published | Yes |

### Fingerprint

### Keywords

- Adaptive algorithms
- Adaptive arrays
- Array processing
- Source estimation

### ASJC Scopus subject areas

- Computer Vision and Pattern Recognition
- Signal Processing
- Software
- Control and Systems Engineering
- Electrical and Electronic Engineering

### Cite this

*Signal Processing*,

*46*(2), 243-248. https://doi.org/10.1016/0165-1684(95)00086-S

**Estimation of powers of uncorrelated sources in linear arrays.** / Ko, C. C.; Liu, Huan.

Research output: Contribution to journal › Article

*Signal Processing*, vol. 46, no. 2, pp. 243-248. https://doi.org/10.1016/0165-1684(95)00086-S

}

TY - JOUR

T1 - Estimation of powers of uncorrelated sources in linear arrays

AU - Ko, C. C.

AU - Liu, Huan

PY - 1995

Y1 - 1995

N2 - The performance of the MUSIC estimator for the powers of uncorrelated sources arriving at a linear array is studied and is compared with the Cramer-Rao bound on the direction estimates of two closely spaced sources investigated in (Swingler, 1993). In general, it is found that if the source directions can be accurately estimated as when the sources are well separated, the estimator will function well and has a percentage variance which depends solely on the number of data samples. However, when the source separation is small and the direction estimates are poor, the normalized standard deviations of the power estimates will increase drastically and may become larger than that of the direction estimates.

AB - The performance of the MUSIC estimator for the powers of uncorrelated sources arriving at a linear array is studied and is compared with the Cramer-Rao bound on the direction estimates of two closely spaced sources investigated in (Swingler, 1993). In general, it is found that if the source directions can be accurately estimated as when the sources are well separated, the estimator will function well and has a percentage variance which depends solely on the number of data samples. However, when the source separation is small and the direction estimates are poor, the normalized standard deviations of the power estimates will increase drastically and may become larger than that of the direction estimates.

KW - Adaptive algorithms

KW - Adaptive arrays

KW - Array processing

KW - Source estimation

UR - http://www.scopus.com/inward/record.url?scp=0029386836&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0029386836&partnerID=8YFLogxK

U2 - 10.1016/0165-1684(95)00086-S

DO - 10.1016/0165-1684(95)00086-S

M3 - Article

AN - SCOPUS:0029386836

VL - 46

SP - 243

EP - 248

JO - Signal Processing

JF - Signal Processing

SN - 0165-1684

IS - 2

ER -