Adversarial method based on chaff interference measured data
A technology of measured data and chaff interference, applied in the field of radar, can solve problems such as unstable echo characteristics, poor practicability, and the anti-interference party cannot obtain key information, achieving effective countermeasures, strong universality, The effect of suppressing the broadening effect
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Embodiment 1
[0065] See figure 1 , figure 1 It is a flow chart of a countermeasure method based on chaff interference measured data provided by an embodiment of the present invention, which includes:
[0066] Step 1: Obtain the echo signal of the radar.
[0067] In this embodiment, the radar echo signal s(t) of a single point target and a single chaff wire can be expressed as:
[0068]
[0069] in, T r is the repetition period; T e is the pulse width; μ=B / T e is the FM slope, and B is the FM bandwidth. It is known that the modulation method of the measured data is chirp, and each frame of data includes N=32 echoes. τ and f d are the time delay and Doppler frequency, respectively.
[0070]
[0071]
[0072] R 0 and R i are the distances between the single-point target and the i-th chaff; v 0 and v i are the speeds of the single-point target and the i-th chaff, respectively; c is the speed of light, f c is the carrier frequency; f di is the velocity fluctuation cause...
Embodiment 2
[0153] The beneficial effects of the present invention will be further described through simulation tests below.
[0154] 1. Test conditions and parameter settings
[0155] In this simulation experiment, a target and two chaffs are used as an example to collect data from Ku-band pulse Doppler radar. The radar monitored the entire process of only existing targets → firing the first chaff round → firing the second chaff round, and observed the entire diffusion process of the chaff round. Each frame of this batch of data includes 32 echoes; the two-dimensional constant false alarm takes 32 protection units and 16 reference units in range Doppler; the clustering radius of the mean shift is 21, and the support vector machine, naive Three classifiers, Bayesian and Random Forest, are used for target recognition.
[0156] 2. Test platform
[0157] Software: Windows 10 Professional 64-bit, MATLAB2020b and its Classification Learner toolbox.
[0158] Hardware: CPU: i9-10980XE; Memor...
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