Passive radar signal detection method based on sequential statistical filtering and binary detection

Abstract

The invention belongs to the technical field of electronic reconnaissance, and particularly relates to a passive radar signal detection method based on sequential statistical filtering and binary detection. According to the invention, after certain speed reduction and signal-to-noise ratio improvement are carried out on low-signal-to-noise-ratio signals in a large instantaneous monitoring bandwidth through channelization preprocessing, binary accumulation detection is combined, and rapid and accurate detection can be realized under a certain low-signal-to-noise-ratio condition. The method adapts to the trend that the sampling rate of a reconnaissance system in the passive radar field is higher and higher, and solves the problem that signal detection is difficult under the condition of low signal-to-noise ratio. On the basis of a relatively stable condition in a channel, a detection threshold is estimated by performing sequential statistical filtering processing on reference data in a parallel sliding window without additional threshold compensation; wherein the parallel pipeline type structure ensures that an adaptive constant false alarm threshold can be quickly obtained under strong noise, the detection and false alarm probability can be further improved by adopting a binary accumulation detection technology, so that the application limitation of an existing detection method is overcome.

Description

technical field [0001] The invention belongs to the technical field of electronic reconnaissance, and in particular relates to a passive radar signal detection method based on sequential statistical filtering and binary detection. Background technique [0002] In recent years, anti-stealth and low probability of intercept (LPI), broadband and ultra-wideband have become the development trend of radar design. In terms of reconnaissance and interception of electronic intelligence, its difficulty is also getting higher and higher. The reconnaissance receiver designed for LPI radar signals has two requirements: one is a wider instantaneous monitoring bandwidth to ensure a higher probability of interception in the frequency domain; the other is the ability to process complex forms of signals. In order to reduce the probability of the radar signal being intercepted by the reconnaissance receiver, the LPI radar transmits a low power signal, and at the same time it uses a special pu...

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Problems solved by technology

[0004] By searching the prior art documents, it was found that "Passive Radar Detection With NoisyReference Channel Using Principal Subspace Similarity" (vol.54, no.1, pp. 18-36, Feb.2018, doi:10.1109 / TAES.2017.2730998) developed a new detector using the main left singular vector cross-correlation of the reference signal and the monitor signal plus noise matrix. In practice, the detection The need for SNR-dependent thresholds for Constant False Alarm Probability (CFAR) operation complicates and limits their use in practice.

Xu Zhan proposed a low-SNR signal detection algorithm based on sparse wavelet transform in "Journal of Instrumentation" (2013,34(04):825-30). The signal-to-noise ratio detection method can significantly improve the signal reconstruction error by setting the iteration threshold reasonably to achieve the effect of signal noise reduction, and at the same time reduce the system sampling rate and implementation complexity. However, this method requires prior information of the pulse waveform as a premise. And it is greatly affected by the choice of iteration threshold

"Optimization and Application of Low Interception Probability Radar Signal Detection Method" published in "Optical Precision Engineering" (2014,22(11):3122-8) by Li Na et al. proposed an optimized fast Fourier transform (FFT ) accumulation algorithm (FFTAccumulation Method, FAM), which uses a parallel pipeline structure to perform FFT operations on sampled signals, and realizes blind detection of LPI signals; compared with traditional FAM algorithms, its complexity and real-time performance have been greatly improved; but The limitation is that FFT transformation needs to be performed on the sampling points in the window every time. Once the data volume of the sampling points is large, the computational complexity and time will increase accordingly.

[0005] The search results of the existing literature show that the existing signal detection methods for passive radar signals under the condition of low signal-to-noise ratio have certain limitations. data etc.

In general, the current signal detection methods are difficult for low signal-to-noise ratio signal detection, and lack some fast detection methods for large bandwidth signals with low signal-to-noise ratio. The fast and accurate detection method is based on channelization technology, sequential statistical filtering and binary accumulation detection technology to quickly obtain detection results, which solves the problem of high algorithm complexity and reference The technical problem that the large amount of data cannot quickly obtain the test results

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