Micro-Doppler processing for ultra-wideband radar data

In this paper, we describe an operational pulse Doppler radar imaging system for indoor target localization and classification, and show how a target's micro-Doppler signature (μDS) can be processed when ultra-wideband (UWB) waveforms are employed. Unlike narrowband radars where time-frequency signal representations can be applied to reveal the target time-Doppler frequency signatures, the UWB system permits joint range-time-frequency representation (JRTFR). JRTFR outputs the data in a 3D domain representing range, frequency, and time, allowing both the μDS and high range resolution (HRR) signatures to be observed. We delineate the relationship between the μDS and the HRR signature, showing how they would form a complimentary joint feature for classification. We use real-data to demonstrate the effectiveness of the UWB pulse-Doppler radar, combined with nonstationary signal analyses, in gaining valuable insights into human positioning and motions.

[1]  F. Ahmad,et al.  Dual-Frequency Radars for Target Localization in Urban Sensing , 2009, IEEE Transactions on Aerospace and Electronic Systems.

[2]  Moeness G. Amin,et al.  Multipath Model and Exploitation in Through-the-Wall and Urban Radar Sensing , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[3]  A. Zoubir,et al.  Through-the-Wall Radar Imaging , 2010 .

[4]  Hao Ling,et al.  Time-Frequency Transforms for Radar Imaging and Signal Analysis , 2002 .

[5]  Yazhou Wang,et al.  Micro-Doppler signatures for intelligent human gait recognition using a UWB impulse radar , 2011, 2011 IEEE International Symposium on Antennas and Propagation (APSURSI).

[6]  Bijan G. Mobasseri,et al.  Robust Through-the-Wall Radar Image Classification Using a Target-Model Alignment Procedure , 2012, IEEE Transactions on Image Processing.

[7]  Karl Woodbridge,et al.  Radar Micro-Doppler Signature Classification using Dynamic Time Warping , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[8]  Irena Orovic,et al.  A new approach for classification of human gait based on time-frequency feature representations , 2011, Signal Process..

[9]  H. Wechsler,et al.  Analysis of micro-Doppler signatures , 2003 .

[10]  Victor C. Chen Joint time-frequency analysis for radar signal and imaging , 2007, 2007 IEEE International Geoscience and Remote Sensing Symposium.

[11]  Moeness G. Amin,et al.  Change Detection Analysis of Humans Moving Behind Walls , 2013, IEEE Transactions on Aerospace and Electronic Systems.

[12]  Brian D. Rigling,et al.  Micro-range/micro-Doppler feature extraction and association , 2011, 2011 IEEE RadarCon (RADAR).

[13]  F. Groen,et al.  Human walking estimation with radar , 2003 .

[14]  J.-M. Nicolas,et al.  Micro-Doppler analysis of wheels and pedestrians in ISAR imaging , 2008 .

[15]  Youngwook Kim,et al.  Human Activity Classification Based on Micro-Doppler Signatures Using a Support Vector Machine , 2009, IEEE Transactions on Geoscience and Remote Sensing.

[16]  M. Amin Through-the-Wall Radar Imaging , 2011 .

[17]  Qun Zhang,et al.  Micro-Doppler Effect Analysis and Feature Extraction in ISAR Imaging With Stepped-Frequency Chirp Signals , 2010, IEEE Transactions on Geoscience and Remote Sensing.

[18]  Yang Li,et al.  Doppler-based detection and tracking of humans in indoor environments , 2008, J. Frankl. Inst..