Time-frequency curve extraction method for precession targets based on frequency domain entropy
A time-frequency and frequency-domain technology, applied in the field of target recognition and time-frequency curve extraction of precession targets, can solve problems such as difficult time-frequency curve extraction, errors, and increased computational complexity, so as to improve the matching success rate and reduce complexity , the effect of reducing the amount of calculation
Active Publication Date: 2018-04-20
XIDIAN UNIV
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[0005] One is that the space cone target echo signal received by the radar is the superposition of the echo signals of each scattering center on the cone, so that the time-frequency curves of each scattering center intersect each other in the time-frequency diagram, so it is difficult to Direct extraction of time-frequency curves for each scattering center
[0006] The second is that all the micro-movement feature extraction methods of time-frequency images need to solve the problem of frequency point correlation, and frequency point correlation has two disadvantages: on the one hand, frequency point correlation is easy to generate errors at the intersection points of time-frequency curves of different scattering centers, Lead to the failure of micro-motion feature extraction; on the other hand, time-frequency correlation will increase the computational complexity and reduce the efficiency of micro-motion feature extraction
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[0022] The present invention will be further described in detail below in conjunction with the accompanying drawings.
[0023] Step 1: Calculate the time-frequency signal P according to the echo signal received by the radar.
[0024] 1a) The radar receives the echo signal of the space cone target: sr={s 1 ,s 2 ,s 3 ,...,s i ,...,s H}, where s i Represents the i-th pulse, i∈[1,H], H represents the number of echoes;
[0025] 1b) Perform short-time Fourier transform on the echo signal sr to obtain a time-frequency signal: P=STFT(sr), where STFT(Δ) represents the short-time Fourier transform, where P is the short-time Fourier transform of the echo signal The time-frequency signal obtained by Liye transform.
[0026] Step 2: Perform constant false alarm processing on the obtained time-frequency signal.
[0027] 2a) Threshold value D is set according to the false alarm probability of radar, such as the radar false alarm probability in the present invention is 10 -6 , then t...
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The invention discloses a time-frequency curve extraction method for precession targets based on frequency domain entropy, and mainly solves the large calculated quantity and low efficiency of spectrum correlation calculation in the prior art. The method comprises steps of: 1, subjecting the envelope of a radar echo signal to FFT to obtain a time-frequency signal; 2, performing constant false alarm on the time-frequency signal at each moment by a constant false alarm algorithm to obtain a series of frequency points at each moment; 3, performing agglutination on the series of frequency points obtained at each moment to obtain one or two time frequency points at each moment; and 4, matching the one or two time frequency points by using the frequency domain entropy to obtain a curve, and automatically forming another curve by using the remaining points. The method reduces the calculation amount, improves the correlation efficiency, improves the matching success rate, and can be used for target recognition.
Description
technical field [0001] The invention belongs to the technical field of radar, in particular to a time-frequency curve extraction method of a precession target based on frequency domain entropy, which can be used for target recognition. Background technique [0002] When the space cone target moves, it will rotate and vibrate on its running track, these tiny movements, these tiny movements are called fretting. Micro-movement is a very common phenomenon. Generally, moving objects will be accompanied by micro-motion, such as: the swing of limbs when people walk, the chest vibration caused by human breathing and heartbeat, the rotation of helicopter rotors, the rotation of antennas, and the wheels of vehicles when they are moving forward. The rotation of the engine, the vibration when the engine is working, etc. The micro-Doppler features produced by the micro-motion of the target can reflect the geometric composition and motion characteristics of the target's structural compon...
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IPC IPC(8): G01S13/52
CPCG01S13/52
Inventor 纠博王一鸣时玉春刘宏伟王鹏辉
Owner XIDIAN UNIV