IEEE - Aerospace and Electronic Systems - July 2021 - 40

ASurveyofArtificial Intelligence Approaches for Target Surveillance With Radar Sensors
classification, which represents a prime example for the
application of AI. For this reason, we focused on presenting
the key ideas of the large amount of literature available
to SAR/ISAR and micro-Doppler based classification
while describing our own insights. Finally, we analyzed
the impact and value of AI approaches for target tracking.
Therefore, we investigated the different parts of tracking
approaches and presented for each part past and recent
approaches aiming at the improvement of tracking by
algorithms. Moreover, we discussed the potential of AI
supported tracking approaches in practice and outlined
our findings in this area.
Taken together, we highlighted, to the best of our
knowledge, the most representative literature as well as
sufficient references to follow up any of the above mentioned
topics. Nevertheless, AI represents a very large
area of research, which is currently evolving at a rapid
pace. Hence, our investigation is by no means complete.
In addition, our focus within this article relied on radar
sensor application for target surveillance. Research developing
AI approaches based on, for example, weather
radars or optical sensors has consequently been omitted.
Thus, future research could, on the one hand, extend the
scope of our investigations toward further sensor application
and on the other hand, deepen certain subareas. In
spite of these limitations, we hope that our article broadens
the understanding of AI approaches for radar sensors
and indicates potential starting points for future work.
REFERENCES
[1] S. Makridakis, " The forthcoming artificial intelligence (AI)
revolution: Its impact on society and firms, " Futures,
vol. 90, pp. 46-60, 2017.
[2] M. Hussain and D. Manhas, " Artificial intelligence for big
data: Potential and relevance, " Int. Acad. Eng. Med. Res.,
vol. 1, no. 1, pp. 1-5, 2016.
[3] I. M. Cockburn, R. Henderson, and S. Stern, " The impact of
artificial intelligence on innovation: An exploratory analysis, "
in TheEconomics ofArtificial Intelligence:AnAgenda,
A. Agrawal, J. Gans and A. Goldfarb, Eds. Chicago, IL,
USA: Univ. ofChicago Press, 2018, pp. 115-146.
[4] IPlytics GmbH, " Who is patenting AI technology?, " 2019.
Accessed: Sep. 3, 2020 [Online]. Available: https://www.
iplytics.com/de/report-de/who-patenting-ai-technology/.
[5] CISTP, " China AI development report 2018, " 2018.
Accessed: Sep. 3, 2020 [Online]. Available: http://www.
sppm.tsinghua.edu.cn/eWebEd./UploadFile/China_AI_
development_report_2018.pdf.
[6] CB Insights, " AI in numbers Q1'20: The impact of Covid19
on global funding, exits, valuations, R&D, and more, "
2020. Accessed: Sep. 3, 2020 [Online]. Available: https://
www.cbinsights.com/research/report/ai-in-numbers-q12020/.
40
[7]
A. Hosny, C. Parmar, J. Quackenbush, L. H. Schwartz, and
H. J. W. L. Aerts, " Artificial intelligence in radiology, "
Nature Rev. Cancer, vol. 18, no. 8, pp. 500-510, 2018.
[8] S. J. Russell and P. Norvig, Artificial Intelligence: A Modern
Approach, 3rd ed. Harlow, U.K.: Pearson Education,
2016.
[9] D. E. O'Leary, " Artificial intelligence and big data, " IEEE
Intell. Syst., vol. 28, no. 2, pp. 96-99, Mar./Apr. 2013.
[10] U. Majumder, E. P. Blasch, and D. A. Garren, Deep Learningfor
Radar andCommunicationsAutomatic Target Recognition.
Norwood, MA, USA: Artech House, 2020.
[11] T. Hastie, R. Tibshirani, and J. Friedman, The Elements of
Statistical Learning, 2nd ed. New York, NY, USA:
Springer Science & Business Media, 2009.
[12] W. Stehwien and S. Haykin, " A statistical radar clutter
classifier, " in Proc. IEEE Nat. Radar Conf., 1989,
pp. 164-169.
[13] C. E. Martin, S. K. Rogers, and D. W. Ruck,
" Nonparametric Bayes error estimation for HRR target
identification, " Appl. Artif. Neural Netw. V, no. 2243,
pp. 2-10, 1994.
[14] L.Breiman,J.H.Friedman,R.A.Olshen, andC.J.Stone,
Classification and Regression Trees.Boca Raton,FL,
USA: CRC Press, 1984.
[15] J. R. Quinlan, C4.5: Programsfor Machine Learning.San
Mateo, CA, USA: Morgan Kaufmann, 1993.
[16] M. Garg and U. Singh, " C & R tree based air target classification
using kinematics, " Int. J. Comput. Commun. Technol.,
vol. 5, no. 2, 2014, Art. no. 2.
[17] T. G. Dietterich, " Ensemble methods in machine
learning, " in Multiple Classifier Systems. vol. 1857, J. Kittler
and F. Roli, Eds., Berlin, Germany: Springer, 2000,
pp. 1-15.
[18] G. Valentini and F. Masulli, " Ensembles of learning
machines, " in Proc. 13th Italian Workshop Neural NetsRevised
Papers, 2002, pp. 3-20.
[19] S. B. Kotsiantis, I. D. Zaharakis, and P. E. Pintelas,
" Machine learning: A review of classification and combining
techniques, " Artif. Intell. Rev., vol. 26, no. 3, pp. 159-
190, 2006.
[20] X. Zhang et al., " A clutter suppression method based on
SOM-SMOTE random forest, " in Proc. IEEE Radar
Conf., 2019, pp. 1-4.
[21] L. W. Jochumsen, J. Ostergaard, S. H. Jensen, C. Clemente,
and M. O. Pedersen, " A recursive kinematic random
forest and alpha beta filter classifier for 2D radar tracks, "
EURASIP J. Adv. Signal Process., vol. 2016, 2016,
Art. no. 82.
[22] S. Liu, H. Li, Y. Zhang, B. Zou, and J. Zhao, " Random
forest-based track initiation method, " J. Eng., vol. 2019,
no. 19, pp. 6175-6179, 2019.
[23] K. Thormann, F. Sigges, andM. Baum, " Learning an object
tracker with a random forest and simulated measurements, "
in Proc. 20th Int. Conf. Inf. Fusion, 2017, pp. 1-4.
IEEE A&E SYSTEMS MAGAZINE
JULY 2021

https://www.iplytics.com/de/report-de/who-patenting-ai-technology/ https://www.iplytics.com/de/report-de/who-patenting-ai-technology/ http://www.sppm.tsinghua.edu.cn/eWebEd./UploadFile/China_AI_development_report_2018.pdf http://www.sppm.tsinghua.edu.cn/eWebEd./UploadFile/China_AI_development_report_2018.pdf http://www.sppm.tsinghua.edu.cn/eWebEd./UploadFile/China_AI_development_report_2018.pdf https://www.cbinsights.com/research/report/ai-in-numbers-q1-2020/ https://www.cbinsights.com/research/report/ai-in-numbers-q1-2020/ https://www.cbinsights.com/research/report/ai-in-numbers-q1-2020/

IEEE - Aerospace and Electronic Systems - July 2021

Table of Contents for the Digital Edition of IEEE - Aerospace and Electronic Systems - July 2021