Classification Based on Jamming Signal Waveforms

Suppressive jamming can be classified into noise amplitude modulation (AM) jamming, noise frequency modulation (FM) jamming, and noise phase modulation (PM) jamming based on the waveform characteristics of the jamming signals. These methods employ noise or noise-like interference signals to obscure or淹没 useful signals, thereby preventing radar systems from detecting target information. The core principle operates on the basis that every radar system contains both external and internal noise, and target detection is performed within this noisy environment using specific probability-based detection criteria. Typically, if the target signal energy (S) compared to the noise energy (N) - expressed as the signal-to-noise ratio (S/N) - exceeds the detection threshold (D), the system can achieve the required detection probability (Pd) for identifying target echoes under a predetermined false alarm probability (Pfa). This condition is commonly referred to as "detectable target." Conversely, if the ratio falls below the threshold, the target is considered "undetectable."

Moreover, the characteristics of jamming signals significantly impact the effectiveness of suppressive jamming. For instance, frequency offset and phase modulation properties of jamming signals can influence radar target detection capabilities. When designing jamming systems, engineers must account for these characteristics and implement corresponding strategies to enhance jamming effectiveness. In code implementation, this involves configuring waveform parameters through modulation functions (e.g., MATLAB's ammod, fmmod, pmmod) and optimizing frequency sweeping algorithms.

Countermeasures against suppressive jamming continue to evolve. Radar systems can employ frequency hopping techniques, implement phased array antennas, and utilize adaptive signal processing methods to mitigate jamming effects. Advanced implementations incorporate sophisticated signal processing algorithms and machine learning technologies to improve target detection and recognition capabilities. For example, developers might use spectral analysis functions like fft combined with SVM classifiers for jamming identification.

In conclusion, suppressive jamming plays a critical role in radar systems by effectively preventing target detection and safeguarding sensitive information. Therefore, comprehensive consideration of suppressive jamming and appropriate countermeasures must be integrated into both the design and application phases of radar system development.