Research Of DRFM Electronic Jamming Detection And Identification Algorithm

In modern warfare, with the emergence and development of digital radio frequency memory(DRFM), radar electronic jamming technique has entered the age of coherent interference. Different kinds of DRFM electronic jamming applied in radar systerms have brought severe challenges along with threats. In order to take optimal electronic counter-countermeasures to cancel the effect of the DRFM jamming and improve the utilization rate of radar resources, the existence and the type of the jamming must be determined at first. Therefore, being the prerequisite and foundation of anti-jamming technique, it has gradually become a new research hotspot in the field of electronic countermeasures to study the detection and recognition algorithm of the DRFM jamming.Focusing on the detection and recognition problem of the DRFM jamming, this paper carries out research on the six kinds of typical DRFM electronic jamming subclasses. The specific works of this paper are as follows:1. The process and mechanism of six typical DRFM electronic jamming(including range gate pull jamming, range false target jamming, velocity gate pull jamming, velocity false target jamming, smeared spectrum jamming and chopping and interleaving jamming) are studied. Their mathematic signal models are also established. At the same time, the influence of these six typical DRFM electronic jamming on radar detection is discussed by simulations analysis.2. In view of the range deception jamming, using the nuance between the jamming signal and the actual target signal caused by phase quantization and taking advantage of the theories of signal detection, the generalized likelihood detection algorithm based on signal cone and the two-step detection algorithm based on error angle are studied. According to the characteristic that the jamming and the actual target overlap completely in time domain, the energy detection algorithm of velocity deception jamming is also studied. The simulation results verify the effectiveness of these detection algorithms.3, Aiming at typical intensive false target jamming,a generalized likelihood detection algorithm based on jamming reconstruction is proposed. In this method, all the unknown amplitude parameters of radar received signal and the jamming signal are estimated which improves the jamming detection performance significantly.4. The recognition algorithm of range deception jamming and velocity deception jamming is studied by extracting characteristic parameters. In view of the SMSP jamming, thanks to the differences of time-frequency characteristics between the jamming signal and the actual target signal, the four methods are proposed, i.e. the ambiguity function, the Wigner-Ville distribution, the PWVD-Hough transform and the PWVD-Radon transform. These methods transformed the jamming signal and actual target signal into the domain where they can be separated, then, the SMSP jamming can be identified efficiently by extracting the characteristic parameters. Similarly, using its piecewise time-frequency characteristic, the recognition algorithm of C&I jamming based on the ambiguity function is studied. The simulation results show that the jamming identification algorithms can effectively identify the smeared spectrum jamming and the chopping and interleaving jamming, and estimate the jamming parameters.