Signal in-pulse characteristic real-time analysis and processing method based on FPGA high-speed preprocessing

Abstract

The invention realizes a signal in-pulse characteristic real-time analysis and processing method based on FPGA high-speed preprocessing, which is applied to a fine analysis subsystem of a passive detection system, determines signal types of unknown signals rapidly and carries out parameter estimation. The signal in-pulse characteristic real-time analysis and processing method provided by the invention can realize the effects of estimating intermediate frequency data in a pipeline analysis concern range (frequency, pulse width and amplitude) in an acquisition mode, and displaying PDW frequency, pulse width and amplitude information and an in-pulse characteristic graphical analysis result; and the signal in-pulse characteristic real-time analysis and processing method can analyze the in-pulse characteristics of the PDW corresponding to the intermediate frequency data in real time when a user selects the designated PDW in a playback mode. The signal in-pulse characteristic real-time analysis and processing method utilizes the integration of an FPGA chip and analysis software, accelerates the analysis speed, and meets the requirement of real-time performance.

Description

technical field [0001] The technology belongs to the field of passive radar data processing of passive detection technology. Background technique [0002] Radar signal intra-pulse modulation feature recognition technology is an important means of target signal recognition. It refers to the intra-pulse modulation feature recognition of these signals on the basis of intercepted radar signals in time domain, frequency domain and air domain, and extracts characteristic parameters. [0003] There are many methods for intrapulse feature analysis of radar signals, and the current popular algorithms are mainly divided into time domain analysis method, modulation domain analysis method, and time-frequency domain analysis method. Since intravein feature extraction is a highly confidential military technique, relatively few foreign research results appear in open literature, and most of the public ones are intravein feature extraction methods based on the time-frequency domain. In the...

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Problems solved by technology

[0006] (1) The existing algorithm needs to intercept the signal to have a certain signal-to-noise ratio requirement, and when the signal-to-noise ratio is too low, misjudgment often occurs

[0007] (2) There are many kinds of intra-pulse modulation methods of radar signals, and various intra-pulse modulation feature analysis and recognition algorithms need to be used for parallel processing. At present, there are few domestic research results on the comprehensive judgment of the analysis and discrimination results of the algorithm.

[0009] (4) At present, it is still a difficult task to infer information such as the carrier weapon platform and threat level indirectly through the identification of radar signal intrapulse modulation characteristics

[0011] In principle, the speed of intrapulse feature analysis can be improved by improving graphics card performance, computer CPU performance, increasing memory capacity, updating algorithms, etc., but the room for improvement is extremely limited. In the face of complex, changeable and unknown radar signals It is difficult to realize the real-time requirement of intra-pulse feature analysis

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