Simplified High-Resolution Template Simulator in SAR Seeker HWIL Simulation

Document Type : Original Article

Authors

1 telecommunications group, electrical eng. dep., Babol Noshirvani University of Technology, Babol, Iran

2 telecommunications group, electrical eng. dep., Babol Noshirvani university of technology, Babol, Iran

Abstract

With the development of high resolution synthetic aperture radar (SAR) technology, new challenges are emerging in the test stage of the SAR seekers using hardware in the loop (HWIL) simulation. In fact, in order to establish a confident HWIL simulation, the simulator should also generate the echo signal with the same resolution the SAR performs image processing. Echo signal generation by high resolution target template faces the issue of dealing with the incremental computation resources and contradicts with the real time requirement of HWIL simulation. In this paper, the potential of a very high resolution SAR test experiment by means of a lowered resolution simulator in HWIL simulation will be discussed. As the first step, we put forward a simple method of template resolution reduction to overcome the high time-consuming and computational resource requirement of high resolution SAR HWIL simulation and then theoretically explore the influence of template resolution reduction on the final SAR imaging. In this way, the resolution of the SAR seeker is kept fixed, and the scene simulator is forced to generate the echo signal at a lower resolution. In comparison to conventional echo signal generation, the proposed method can clearly better manage the hardware requirement of HWIL simulation and obtain acceptable imaging results. The results of the proposed method are compared with the reference one in terms of structural similarity index (SSIM) and the peak signal-to-noise ratio (PSNR) as performance evaluation criteria. Simulation results on an actual SAR template verify the good performance of the approach.

Keywords

Main Subjects

References

[1] ENTEZARI, R.; RASHIDI, A. J. Inverse Synthetic Aperture Radar (ISAR) Imaging of Targets with Non-Uniform Motion. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 2017, 47.2: 391-400 (in Persian).‏
[2] KIESBYE, Jonis, et al. Hardware-in-the-loop and software-in-the-loop testing of the move-ii cubesat. Aerospace, 2019, 6.12: 130.‏
[3] BIRKENHAUER, Christoph, et al. A simple and versatile concept to improve dynamic range and enable target angle adaptability in radar target simulators. IEEE Journal of Microwaves, 2023.‏
[4] DIEWALD, Axel, et al. Radar target simulation for vehicle-in-the-loop testing. Vehicles, 2021, 3.2: 257-271.‏
[5] SCHOEDER, Pirmin, et al. Flexible direction-of-arrival simulation for automotive radar target simulators. IEEE Journal of Microwaves, 2021, 1.4: 930-940.‏
[6] IBERLE, Johannes; RIPPL, Patrick; WALTER, Thomas. A near-range radar target simulator for automotive radar generating targets of vulnerable road users. IEEE Microwave and Wireless Components Letters, 2020, 30.12: 1213-1216.‏
[7] SCHOEDER, Pirmin, et al. A unified model of coherent direction-of-arrival simulation for radar target simulators. IEEE Transactions on Aerospace and Electronic Systems, 2023, 59.4: 4738-4743.‏
[8] SCHOEDER, Pirmin, et al. Multitarget simulator for automotive radar sensors with unknown chirp-sequence modulation. IEEE Microwave and Wireless Components Letters, 2021, 31.9: 1086-1089.‏
[9] DIEWALD, Axel, et al. Range Doppler migration synthesis for realistic radar target simulation. In: 2021 IEEE Topical Conference on Wireless Sensors and Sensor Networks (WiSNeT). IEEE, 2021. p. 56-58.‏
[10] FRANCESCHETTI, Giorgio, et al. SARAS: A synthetic aperture radar (SAR) raw signal simulator. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30.1: 110-123.‏
[11] FRANCESCHETTI, Giorgio; MIGLIACCIO, Maurizio; RICCIO, Daniele. SAR raw signal simulation of actual ground sites described in terms of sparse input data. IEEE Transactions on Geoscience and Remote Sensing, 1994, 32.6: 1160-1169.‏
[12] FRANCESCHETTI, Giorgio, et al. SARAS: A synthetic aperture radar (SAR) raw signal simulator. IEEE Transactions on Geoscience and Remote Sensing, 1992, 30.1: 110-123.‏
[13] TOREINIA, R.; KAZEROONI, M.; FALLAH, M. Analysis and Evaluation of Important Antenna and Radome Parameters Effect on the Angle Measurement of a Monopulse Radar Simulator for a Projectile Platform. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 2018, 47.4: 1381-1393 (in Persian).‏
[14] KIM, Duk-jin, et al. Melt pond mapping with high-resolution SAR: The first view. Proceedings of the IEEE, 2013, 101.3: 748-758.‏
[15] SAEEDI, Jamal. Feasibility study and conceptual design of missile-borne synthetic aperture radar. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 50.3: 1122-1133.‏
[16] REALE, Diego, et al. Tomographic imaging and monitoring of buildings with very high resolution SAR data. IEEE Geoscience and remote sensing letters, 2011, 8.4: 661-665.‏
[17] ZONGBO, Wang, et al. Design and application of DRFM system based on digital channelized receiver. In: 2008 International Conference on Radar. IEEE, 2008. p. 375-378.‏
[18] SHU, Ting, et al. Development of multichannel real-time Hardware-in-the-Loop radar environment simulator for missile-borne Synthetic Aperture Radar. In: 2015 IEEE Radar Conference (RadarCon). IEEE, 2015. p. 0368-0373.‏
[19] HE, Zhihua, et al. A hardware-in-loop simulation and evaluation approach for spaceborne distributed SAR. In: 2011 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2011. p. 886-889.‏
[20] ZHANG, Shunsheng; CHEN, Juan. A echo simulation algorithm for natural scene. In: 2008 International Conference on Radar. IEEE, 2008. p. 464-468.‏
[21] SHU, Ting, et al. Development of multichannel real-time Hardware-in-the-Loop radar environment simulator for missile-borne Synthetic Aperture Radar. In: 2015 IEEE Radar Conference (RadarCon). IEEE, 2015. p. 0368-0373.‏
[22] BRUNET, Dominique; VRSCAY, Edward R.; WANG, Zhou. On the mathematical properties of the structural similarity index. IEEE Transactions on Image Processing, 2011, 21.4: 1488-1499.‏
[23] ZUJOVIC, Jana; PAPPAS, Thrasyvoulos N.; NEUHOFF, David L. Structural texture similarity metrics for image analysis and retrieval. IEEE Transactions on Image Processing, 2013, 22.7: 2545-2558.‏
[24] C. W. Kok and W. S. Tam, “Image Quality,” in Digital Image Interpolation in Matlab, John Wiley & Sons, 2019, ch. 3, pp. 71–90.
[25] FARDO, Fernando A., et al. A formal evaluation of PSNR as quality measurement parameter for image segmentation algorithms. arXiv preprint arXiv:1605.07116, 2016.‏
[26] HORE, Alain; ZIOU, Djemel. Image quality metrics: PSNR vs. SSIM. In: 2010 20th international conference on pattern recognition. IEEE, 2010. p. 2366-2369.

Files

Share

How to cite

Statistics