Abstract: ‍ ‍In the field of modern electronic warfare， interrupted-sampling repeater jamming based on Digital Radio Frequency Memory （DRFM） has gained prominence owing to its ability to create novel coherent jamming effects. This technique confuses enemy radar by intermittently sampling and retransmitting signals， disrupting their operations. Interrupted-sampling repeater jamming， with its strong correlation and rapidly changing parameter features， can effectively suppress and deceive radar systems by optimizing the width， numbers， and forwarding times of jamming slices， posing a serious challenge to the security of contemporary radar systems. Interrupted-sampling repeater jamming exhibits a high degree of complexity and rapid change， creating immense challenges for traditional， static interference mitigation methods. These methods are frequently unable to adapt to the swiftly evolving interference environment， making it difficult to ensure sustained， high-efficiency performance. To counter these changes effectively， it is crucial to implement a far more flexible strategy： utilizing known interference parameters as a basis for decision-making and dynamically adjusting and optimizing interference countermeasures. The capability of such strategies to be dynamically tuned enables them to quickly adapt to changes in the environment， thereby providing a solution that is more stable， reliable， and effective in the long term. The article proposes a parameter estimation method for interrupted-sampling repeater jamming based on dechirp processing combined with Short-Time Fourier Transform （Dechirp-STFT）. Initially， the jamming signal was processed with dechirp processing， and a time-frequency analysis was performed on the processed signal using STFT. The key in this step was to generate a time-frequency distribution map that reflected the characteristics of jamming duration and delay. A coarse estimation of the jamming parameters was made through binarization of the time-frequency distribution map and based on the characteristics of signal delay and duration， determining the number of jamming slices. Subsequently， this study proposes a method that is built upon the coarse estimation information to further enhance the precision and performance of parameter estimation in low jam-to-noise ratio （JNR） environments. This involves processing the received echo signal with Time-Domain Deconvolution （TDC）. A more accurate calculation of the number of jamming transmissions and the width of jamming slices was achieved by analyzing the logarithm and duration of the impulse responses obtained after TDC processing. Lastly， this study validates the effectiveness of the proposed algorithm through Monte Carlo simulation experiments and actual measured data. Even under low JNR conditions， the parameter estimation method maintains excellent performance. The experimental results show that when the JNR reached 5 dB， the method could estimate the number of jamming repetitions with more than 80% accuracy and had kept the estimation error of the slice width within $\mathrm{0.07}\mathrm{\mu }\mathrm{s}$， providing more precise and reliable prior information for anti-interrupted-sampling repeater jamming techniques. In conclusion， the parameter estimation method proposed in this article offers strong technical support for radar systems facing complex intermittent sampling repeater jamming. With the continuous development of electronic warfare and technological progress， the parameter estimation method introduced in this paper is expected to be widely applied in future radar and electronic warfare systems， making a positive contribution to enhancing the survivability and anti-jamming performance of systems.