A Space-Time Reverberation Model for Moving Target Detection

Abstract

In recent years, moving target detection methods based on low-rank and sparse matrix decomposition have been developed, and they have achieved good results. However, there is not enough interpretation to support the assumption that there is a high correlation among the reverberations after each transmitting pulse. In order to explain the correlation of reverberations, a new reverberation model is proposed from the perspective of scattering cells in this paper. The scattering cells are the subarea divided from the detection area. The energy fluctuation of a scattering cell with time and the influence of the neighboring cells are considered. Key parameters of the model were analyzed by numerical analysis, and the applicability of the model was verified by experimental analysis. The results showed that the model can be used for several simulations to evaluate the performance of moving target detection methods.

Keywords

Space-time reverberation / Model scattering cell / Energy fluctuation / Moving target detection

References

[1] Candès EJ, Li X, Ma Y, Wright J. Robust principal component analysis. J ACM, 2011, 58(3): 1-37

[2] Chandrasekaran V, Sanghavi S, Parrilo PA, Willsky AS. Rank-sparsity incoherence for matrix decomposition. SIAM J Optim, 2011, 21(2): 572-596

[3] Ge FX, Chen Y, Li W (2017) Target detecton and tracking via structured convex optimization. 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), New Orleans, pp 426–430

[4] Grigor’ev VA, Kuz’kin VM, Petnikov BG. Low-frequency bottom reverberation in shallow-water ocean regions (article). Acoust Phys, 2004, 50(1): 37-45

[5] Halko N, Martinsson PG, Tropp JA. Finding structure with randomness: probabilistic algorithms for constructing approximate matrix decompositions. SIAM Rev, 2011, 53(2): 217-288

[6] Harrison CH. Closed-form expressions for ocean reverberation and signal excess with mode stripping and Lambert’s law. J Acoust Soc Am, 2003, 114(5): 2744-2756

[7] Khorshidi S. The principal component inverse algorithm for detection in the presence of reverberation using autoregressive model. Iran J Sci Technol-Trans Electr Eng, 2014, 38(E1): 91-97

[8] Lee DH, Shin JW, Do DW, Choi SM, Kim HN. Robust LFM target detection in wideband sonar systems. IEEE Trans Aerosp Electron Syst, 2017, 53(5): 2399-2412

[9] Li W, Subrahmanya N, Xu F (2012) Online subspace and sparse filtering for target tracking in reverberant environment. Proceedings of the IEEE Sensor Array and Multichannel Signal Processing Workshop (2):329–332. https://doi.org/10.1109/SAM.2012.6250502

[10] Lingevitch JF, Song HC, Kuperman WA. Time reversed reverberation focusing in a waveguide. J Acoust Soc Am, 2002, 111(6): 2609-2614

[11] Pan X, Li CX, Xu YX, Xu W, Gong XY. Combination of time-reversal focusing and nulling for detection of small targets in strong reverberation environments. IET Radar Sonar Navig, 2014, 8(1): 9-16

[12] Saintval WJ, Hayward TJ (2011) Modulation of a high-frequency shallow-water acoustic channel by sea surface waves: 3-D PE-based modeling. OCEANS 2011 IEEE - Spain, Santander, pp 1–6

[13] Shang EC, Gao T, Wu J. A shallow-water reverberation model based on perturbation theory. IEEE J Ocean Eng, 2008, 33(4): 451-461

[14] Weichang L, Subrahmanya N, Feng X (2012) Online subspace and sparse filtering for target tracking in reverberant environment. 2012 IEEE 7th Sensor Array and Multichannel Signal Processing Workshop (SAM), Hoboken, pp 329–332

[15] Wu JR, Shang EC, Gao TF. A new energy-flux model of waveguide reverberation based on perturbation theory. J Comput Acoust, 2010, 18(03): 209-225

[16] Yin J, Liu B, Zhu G, Xie Z. Moving target detection using dynamic mode decomposition. Sensors, 2018, 18(10): 3461

[17] Yu G, Piao SC. Multiple moving targets detection and parameters estimation in strong reverberation environments. Shock Vib, 2016, 2016: 1-10 Article ID 5274371

[18] Yu G, Piao SC, Han X. Fractional Fourier transform-based detection and delay time estimation of moving target in strong reverberation environment. Iet Radar Sonar Navig, 2017, 11(9): 1367-1372

[19] Zhou JX, Zhang XZ. Integrating the energy flux method for reverberation with physics-based seabed scattering models: modeling and inversion. J Acoust Soc Am, 2013, 134(1): 55-66

[20] Zhou T, Tao D, Wu X. Manifold elastic net: a unified framework for sparse dimension reduction. Data Min Knowl Disc, 2011, 22(3): 340-371

[21] Zhu QY, Li YC, Jiang YL. Zhang WJ, Yang XK, Xu ZX, An P, Liu QZ, Lu Y. Line-type moving object detection for sonar images. Advances on digital television and wireless multimedia communications, 2012, Berlin, Berlin: Springer-Verlag, 189-196