Determination of Fast-Moving Objects’ Speed and Range with Linear Frequency Modulation Continuous Wave Radar Using Autocorrelation Scheme

Introduction. A hardware basis of modern Advanced Driver Assistance Systems (ADAS) consists of millimeterrange radars, characterized by a relatively short range (meters – tens of meters). At the same time, improving of traffic safety requires to increase the range at least to several hundred meters. The one way to achieve such values is to increase wavelength of a probing signal, to use the centimeter range of wavelengths, for example. The paper represents a detailed description of main steps of signal processing algorithm in the model of the ADAS low-power centimeter range radar, which provides fast-moving objects speed and range definition.

Aim. Development of an algorithm for estimating the range and the speed of targets by an autocorrelation radar with a wide-band continuous linear frequency modulation (linear FM) signal in order to increase the rate of the ADAS system estimates formation.

Materials and methods. The proposed algorithm is based on the methods of primary and secondary digital processing of radar signals. The model of a centimeter-range autocorrelation radar with a broadband continuous linear FM probing signal was used for practical researches. MATLAB software was used to process the received signal samples.

Results. The algorithm has been developed to determine the speed and the range of fast-moving objects in conditions when their movement during the evaluation interval significantly exceeds the radar range resolution. The use of simplified Kalman filtering for inter-period secondary signal processing allowed to increase significantly the stability of the algorithm. In a full-scale experiment using the low-power radar model with continuous radiation of the centimeter range, it was shown that a stable assessment of a real car speed and range was provided at a distance of at least about one kilometer.

Conclusion. The results of the field experiment make it possible to draw conclusions that the proposed algorithm is highly robust even in the absence of inter-period secondary processing. Its usage allows one to improve the stability of the algorithm without considerable additional computational costs. It is possible because near-linear dynamics of the observation object and of the radar carrier makes it sufficient to use a simplified implementation of Kalman filter in the form α-β-algorithm.

1. Global Status Report on Road Safety 2018. Available at: https://www.gihub.org/resources/publications/globalstatus-report-on-road-safety-2018/ (accessed 20.11.2019)

2. Paul A., Chauhan R., Srivastava R., Baruah M. Advanced Driver Assistance Systems. SAE Technical Paper 2016-28-0223. doi: 10.4271/2016-28-0223

3. Hamid U. Z. A., Pushkin K., Zamzuri H., Gueraiche D., Rahman M. A. A. Current Collision Mitigation Technologies for Advanced Driver Assistance Systems – A Survey. PERINTIS eJournal. 2016, vol. 6, no. 2, pp. 78–90. Available at: https://www.researchgate.net/profile/Umar_Zakir_Abdul _Hamid/publication/311981545_Current_Collision_Mitiga tion_Technologies_for_Advanced_Driver_Assistance_Syst ems_-_A_Survey/links/586670d108ae329d62074a57.pdf (accessed 24.03.2020)

4. Ramnath C. P. Advanced Driver Assistance Systems (ADAS). Intern. J. of Advanced Research in Electronics and Communication Engineering (IJARECE). 2015, vol. 4, iss. 10, pp. 2616–2618. Available at: http://ijarece.org/wp-content/uploads/2015/10/IJARECEVOL-4-ISSUE-10-2616-2618.pdf (accessed 24.03.2020)

5. Peng Z., Li C. Portable Microwave Radar Systems for Short-Range Localization and Life Tracking: A Review. Sensors. 2019, vol. 19, iss. 5, p. 1136. doi: 10.3390/s19051136

6. Komzalov A. M., Shilov N. G. Application of Modern Technologies in Car Driver Assistance Systems. Journal of Instrument Engineering. 2017, vol. 60, no. 11, pp. 1077–1082. doi: 10.17586/0021-3454-2017-60-11-1077-1082 (In Russ.)

7. Levanon N., Mozeson E. Radar signals. 1st ed. Hoboken, YJ, John Wiley&Sons., 2004, 411 p.

8. Kupryashkin I. F., Likhachev V. P., Ryazantsev L. B. Malogabaritnye mnogofunktsional'nye RLS s nepreryvnym chastotno-modulirovannym izlucheniem [Small-Sized Multifunction Radars with Continuous Frequency-Modulated Radiation]. Moscow, Radioengineering, 2020, 288 p. (In Russ.)

9. Ryazantsev L. B., Likhachyov V. P. Measuring the Range and Radial Velocity of Objects With a Broadband Linear Frequency Modulation Continuous Wave Radar in the Conditions of Migration of Marks Along the Range Channels. Measurement Equipment, 2017, no. 11, pp. 61–64. (In Russ.)

10. Zaugg E. C., Edwards M. C., Margulis A. The SlimSAR: a Small, Multi-Frequency, Synthetic Aperture Radar for UAS Operation. 9th IEEE Intern. Radar Conf. 2010.10– 14 May 2010, Washington, DC. Piscataway, IEEE, 2010. doi: 10.1109/RADAR.2010.5494612

11. Duersch M. I. BYU MICRO-SAR: A Very Small, Low-Power LFM-CW SAR: Master’s Thesis. Brigham Young University. Provo, UT. 2004. Available at: https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article= 1727&context=etd/ (accessed 01.12.2019)

12. Bogomolov A. V., Kupryashkin I. F., Likhachev V. P., Ryazantsev L. B. Small-Sized Dual-Band SAR for an Unmanned Aircraft Complex. Proc. of the XXIX All-Russ. symp. "Radar research of natural environments". March 25–26, 2015, St. Petersburg. SPb., 2015, vol. 11, pp. 237– 242. (In Russ.)

13. Kupryashkin I. F., Likhachev V. P., Ryazantsev L. B., Belyaev V. V. Pat. RF 2635366 C1 (2006.01). A Method for Determining the Range and Radial Velocity of a Target in a Continuous-Wave Radar and a Device for Realizing It. Publ. 13.11.2017. 7 p. (In Russ.)

14. Kupryashkin I. F., Sokolik N. V. Algorithm of Signal Processing in the Radar System with Continuous Frequency Modulated Radiation for Detection of SmallSized Aerial Objects, Estimation of Their Range and Velocity. Journal of the Russian Universities. Radioelectronics. 2019, vol. 22, no. 1, pp. 39–47. doi: 10.32603/1993- 8985-2019-22-1-39-47 (In Russ.)

15. Kuz'min S. Z. Tsifrovaya radiolokatsiya. Vvedenie v teoriyu [Digital Radar. Introduction to the Theory]. Kiev, Izd-vo KViTs, 2000, 428 p. (In Russ.)

16. Farina A., Studer F. A. Radar Data Processing. Vol. 1. Introduction and Tracking. Research Studies Press LTD, 1985, 325 p.