Radar signal waveform based on Costas and Walsh‐Hadamard codes as electronic counter‐countermeasure

Abstract

Belligerent sides of current military conflicts are first and foremost counting on intelligence, air supremacy, and electromagnetic spectrum dominance. Actual concepts of conducting military operations can be characterised by the massive employment of air defence systems, radars, and electronic warfare systems. An approach is aimed to strengthen air‐defence potential by improving the resilience of pulse radar against electronic warfare threats, such as an electronic attack. To cope with the above‐mentioned situation, a radar intrapulse modulation was designed, where a combination of Costas codes and Walsh‐Hadamard codes is applied. Using a particular waveform together with the proposed model for radar signal processing results in increased resilience against an electronic attack, especially against repeater jamming methods. Furthermore, it is also possible to process radar echoes at low levels of Signal‐to‐Noise Ratio (SNR), which enhances radar electronic counter–countermeasure capability. The main scientific contribution of the paper is in the unique design of the Pulse Compression Filter for Combined Intrapulse Modulation (PCF‐CIM) and in its modelling. Based on the statistical evaluation of results, using the proposed radar waveform together with PCF‐CIM, it is possible to detect radar signals with combined intrapulse modulation in the case of SNR ≥ −14 dB with TPR ≥0.9999 and FPR ≤10−6, where SNR stands for Signal‐to‐Noise Ratio, TPR stands for True Positive Rate, and FPR stands for False Positive Rate.

An improved radar clutter suppression by simple neural network

“…Evaluated statistical parameters during the testing of the algorithms, based on the confusion matrix [29], were defined by the count of [29,30]: a. True Positives (TP)-the radar target is detected and indeed presented in the specific range bin or CUT with the specific Doppler frequency, b.…”

“…Based on the above-mentioned confusion matrix parameters, the operation of the tested algorithms was assessed by the following criteria [30,31]: a. True Positive Rate (TPR) as a measure of occurrence of TP in a reference context defined by…”

“…For further analysis, the ROC curves [30,32] were constructed and the Area Under the ROC Curve (AUC) parameter [30,32] was estimated for four SNR values (10, 15, 20, and 25 dB).…”

“…In the analytical part of the research, AUC was computed via the trapezoidal method for the selected SNR values. The trapezoidal method approximates the integration over an interval by breaking the area down into trapezoids with more easily computable areas expressed as [30,34] follows:…”

“…where a = x 1 < x 2 < … < x M < x Mþ1 = b, and (x mþ1 − x m ) is the spacing between each consecutive pair of points. In our case, for computing the AUC value, we can use the formula [30].…”