D.E. Boriskin1, N.V. Gorbachev2, I.D. Isaev3, A.N. Savelyev4

1–4 Federal State Autonomous Educational Institution for Higher Education Bauman Moscow State Technical University (National Research University) (Moscow, Russia)
1 bde19k023@student.bmstu.ru, 2 gorbachevnv@student.bmstu.ru, 3 isaevid@bmstu.ru, 4 savelyev.an@bmstu.ru

Objects are detected on a digital radar image frame in analyzed windows. The effectiveness of solving the object detection problem is determined by the rule of decision threshold setting, which fixes a constant false alarm rate (CFAR) level.

A quick overview of constant false alarm rate (CFAR) algorithms in terms of unsteady object surveying against the surface background is presented. An adaptive detection algorithm based on guard cells average threshold near cell under test in the analyzed window is proposed.

Detection characteristics have been obtained. The effectiveness of proposed detection algorithm for a multipoint object using guard cells threshold averaging in the analyzed window is shown. The probability of object correct detection increases by the same false alarm rate, especially by low signal-to-noise ratio (SNR) values: to ensure the probability of correct detection of 0.5 and 0.9, the gain in SNR is about 4 dB in the SNR range from 3 to 9 dB.

Proposed algorithm is promising for detecting multipoint objects against the surface background, requires parameters optimization for solving a specific problem (the ratio between bin and pixel resolution, detection objects and analyzed window sizes), that is, algorithm parameters adaptation to the conditions of radar surveillance.

Boriskin D.E., Gorbachev N.V., Isaev I.D., Savelyev A.N. An algorithm for adaptive object detection on radar image frames with guard cells averaging and analysis of its effectiveness. Achievements of modern radioelectronics. 2026. V. 80. № 5. P. 61–71. DOI: https://doi.org/10.18127/j20700784-202605-07 [in Russian]

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