OPTIMAL AND SUBOPTIMAL MICRO-DOPPLER ESTIMATION SCHEMES USING CARRIER DIVERSE DOPPLER RADARS
被引:8
作者:
Setlur, Pawan
论文数: 0引用数: 0
h-index: 0
机构:
Villanova Univ, Radar Imaging Lab, Ctr Adv Commun, Villanova, PA 19085 USAVillanova Univ, Radar Imaging Lab, Ctr Adv Commun, Villanova, PA 19085 USA
Setlur, Pawan
[1
]
Amin, Moeness
论文数: 0引用数: 0
h-index: 0
机构:
Villanova Univ, Radar Imaging Lab, Ctr Adv Commun, Villanova, PA 19085 USAVillanova Univ, Radar Imaging Lab, Ctr Adv Commun, Villanova, PA 19085 USA
Amin, Moeness
[1
]
Alunad, Fauzia
论文数: 0引用数: 0
h-index: 0
机构:
Villanova Univ, Radar Imaging Lab, Ctr Adv Commun, Villanova, PA 19085 USAVillanova Univ, Radar Imaging Lab, Ctr Adv Commun, Villanova, PA 19085 USA
Alunad, Fauzia
[1
]
机构:
[1] Villanova Univ, Radar Imaging Lab, Ctr Adv Commun, Villanova, PA 19085 USA
来源:
2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS
|
2009年
关键词:
Iterative maximum likelihood estimation;
Doppler radar;
Urban sensing;
Micro-Doppler;
D O I:
10.1109/ICASSP.2009.4960321
中图分类号:
O42 [声学];
学科分类号:
070206 ;
082403 ;
摘要:
Carrier diverse radars employing two different frequencies, termed as dual-frequency radars, prove effective in determining the target range in urban sensing and through-the-wall applications. In this paper, we derive the maximum likelihood (ML) estimator for the dual frequency radar returns for a micro-Doppler motion profile, which is commonly exhibited by indoor moving targets. Unlike linear models, the respective ML estimator does not have a closed form. We solve the ML estimator for dual frequency radar operations, using iterative reweighted least squares (IRLS). The ML-IRLS algorithm is applied to experimental radar returns for estimating the motion parameters of indoor targets.