An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm
Abstract
:1. Introduction
2. ISAR Imaging Model of Maneuvering Target
3. Proposed Algorithm Description
3.1. Description of the Proposed RCFT
- Remark 1:
- The RCFT employs the merits of both RCT and FT, and it not only has the same integration time as RCT but also works well as a useful tool for nonstationary signals.
- Remark 2:
- The bilinear cubic phase function in (5) utilizes only one time correlation, which is viewed as a signal energy preservation because each additional one time correlation loses about 4 –5 dB in the SNR threshold [17]. In addition to that, the 2-D coherent integration realized in the proposed RCFT will further enhance the SNR. Therefore, the proposed RCFT algorithm provides a good performance, especially when the SNR is low, see simulation section.
- Remark 3:
- the NUFFT speeds up the Fourier transform along the non-uniformly spaced lag-time axis, which is helpful for algorithm real-time realization.
3.2. Numerical Study of RCFT
3.3. ISAR Imaging for Maneuvering Target Based on the Proposed RCFT Algorithm
- Step 1:
- Perform the range compression and the translational motion compensation including envelope alignment and phase autofocus.
- Step 2:
- Characterize the azimuth signal of a range cell after translational compensation as multi-component QFM signals , and perform NUFFT along the lag time variable to obtain CPF result .
- Step 3:
- Apply the proposed RCFT to the and obtain a three-dimensional data matrix in the Doppler Centroid -polar radius -polar angle domain.
- Step 4:
- Project the three-dimensional data matrix onto the Doppler frequency axis along the polar radius and polar angle , which is obtained by
- Step 5:
- Set a proper extraction threshold or a filter to suppress the residual cross terms and noise in the Doppler centroid frequency dimension. In practice, the threshold is usually determined by subtracting −3~−4.5 dB from the maximal energy.
- Step 6:
- Repeat the process of step 1–step 5 for all range cells, and the final high-resolution ISAR image is thus produced by regrouping all the range-Doppler frequency centroids. Since the proposed method does not require computations such as parameter estimation for each scatterer, it is computationally more efficient than the similar parameter estimation based algorithms. The flowchart of the proposed ISAR imaging algorithm is shown in Figure 6.
3.4. Components Computational Complexity Analysis
4. Simulation Results and Analysis
5. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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Parameters Name | Value |
---|---|
Carrier frequency | 10 GHz |
Transmit bandwidth | 200 MHz |
Pulse repetition | 300 Hz |
Wave length | 0.03 m |
Range sample frequency | 300 MHz |
Effective echo pluses | 512 |
Translational coefficients velocity | 20 m/s |
Translational coefficients acceleration | 2 m/s2 |
Translational coefficients acceleration rate | 2 m/s3 |
Effective rotational motion angular velocity | 0.018 rad/s |
Effective rotational motion acceleration | 0.008 rad/s2 |
Effective rotational motion acceleration rate | 0.002 rad/s3 |
Methods | SNR = 5 dB | SNR = −3 dB | ||
---|---|---|---|---|
Figure | Entropy | Figure | Entropy | |
STFT method in [10] | Figure 10a | 9.905 | Figure 11a | 11.623 |
WVD method in [12] | Figure 10b | 9.170 | Figure 11b | 11.341 |
SPWVD method in [13] | Figure 10c | 7.679 | Figure 11c | 9.208 |
RCD method in [15] | Figure 10d | 7.418 | Figure 11d | 7.637 |
IHAF-ICPF method in [7] | Figure 10e | 4.870 | Figure 11e | 5.619 |
CIGCPF-CICPF method in [9] | Figure 10f | 4.513 | Figure 11f | 5.037 |
Our proposed method | Figure 10g | 4.291 | Figure 11g | 4.372 |
Methods | Runtime |
---|---|
RD algorithm | 0.50 m |
STFT method | 1.24 m |
WVD method | 1.56 m |
SPWVD method | 2.73 m |
RCD method | 5.04 m |
IHAF-ICPF method | 56.23 m |
CIGCPF-CICPF method | 41.78 m |
Our proposed method | 8.35 m |
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Zeng, C.; Qin, M.; Li, D.; Liu, H.; Chai, Y. An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm. Sensors 2018, 18, 2814. https://doi.org/10.3390/s18092814
Zeng C, Qin M, Li D, Liu H, Chai Y. An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm. Sensors. 2018; 18(9):2814. https://doi.org/10.3390/s18092814
Chicago/Turabian StyleZeng, Cao, Mengyi Qin, Dong Li, Hongqing Liu, and Yi Chai. 2018. "An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm" Sensors 18, no. 9: 2814. https://doi.org/10.3390/s18092814
APA StyleZeng, C., Qin, M., Li, D., Liu, H., & Chai, Y. (2018). An Efficient ISAR Imaging of Targets with Complex Motions Based on a Quasi-Time-Frequency Analysis Bilinear Coherent Algorithm. Sensors, 18(9), 2814. https://doi.org/10.3390/s18092814