A Novel Micro-motion Multi-target Wideband Resolution Algorithm Based on Curve Overlap Extrapolation

Jiaqi WEI; Lei ZHANG; Hongwei LIU; Jialian SHENG

doi:10.11999/JEIT190033

Volume 41 Issue 12

Dec. 2019

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Article Navigation > Journal of Electronics & Information Technology > 2019 > 41(12): 2889-2895

Jiaqi WEI, Lei ZHANG, Hongwei LIU, Jialian SHENG. A Novel Micro-motion Multi-target Wideband Resolution Algorithm Based on Curve Overlap Extrapolation[J]. Journal of Electronics & Information Technology, 2019, 41(12): 2889-2895. doi: 10.11999/JEIT190033

Citation:

Jiaqi WEI, Lei ZHANG, Hongwei LIU, Jialian SHENG. A Novel Micro-motion Multi-target Wideband Resolution Algorithm Based on Curve Overlap Extrapolation[J]. Journal of Electronics & Information Technology, 2019, 41(12): 2889-2895. doi: 10.11999/JEIT190033

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A Novel Micro-motion Multi-target Wideband Resolution Algorithm Based on Curve Overlap Extrapolation

doi: 10.11999/JEIT190033

Jiaqi WEI^{1, 2},
Lei ZHANG^{1, 2
,
,},
Hongwei LIU^{1, 2},
Jialian SHENG³

1.
National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China
2.
Collaborative Innovation Center of Information Sensing and Understanding at Xidian University, Xi’an 710071, China
3.
Shanghai Radio Equipment Research Institute, Shanghai 201109, China

Funds: The National Natural Science Foundation of China (61771372, 61771367), The Natural Science Foundation of Shanghai (16ZR1434900)

Received Date: 2019-01-15
Rev Recd Date: 2019-04-24

Available Online: 2019-05-22

Publish Date: 2019-12-01

Abstract

Abstract

To solve the problem that the traditional micro-Doppler feature extraction technologies are generally hard to achieve resolution and parameter estimation of multi-target, a novel curve overlap extrapolation algorithm for wide-band resolution of micro-motion multi-target is proposed. According to the relative distance between filtering data points and the historical slope information of each curve, the point trace behind the overlapping location can be extrapolated to realize data association of micor-motion curve for each signal component. On this basis, the multi-target resolution can be realized by analyzing the difference of micor-motion characteristics between each curve. Extensive simulation experiments are provided to illustrate the effectiveness and robustnees of the proposed algorithm.
- Multi-target resolution,
- Micro-motion feature extraction,
- Data association,
- Parameter estimation

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References(19)

References

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