Bipolar ultra-wide spectrum ultra-narrow pulse trailing suppression method

Abstract

The asymmetry and trailing effect of a bipolar impulse signal in a time domain results in abnormal extraction of information such as the size of a target, and effective recognition of the target is difficult to realize. The invention provides a bipolar ultra-wide-spectrum ultra-narrow pulse trailing suppression method based on bipolar signal characteristics aiming at the serious trailing effect when an impulse system radar adopts bipolar ultra-wide-spectrum ultra-narrow pulse target detection, and solves the problem that the main-to-auxiliary ratio of a target is reduced due to trailing and the like based on frequency domain compensation of Hilbert transform. Normal extraction of feature information such as target size is realized, and a foundation is laid for ultra-wide spectrum signal target identification.

Description

Technical Field

[0001] The invention belongs to the field of detection technology, and in particular relates to a method for suppressing tailing of a bipolar ultra-wide spectrum extremely narrow pulse. Background Art

[0002] Ultra-wideband technology has the characteristics of insensitivity to channel fading, low power spectrum density of transmitted signals, and low system complexity, and has received increasing attention in the field of radar detection. Among them, the impulse-based ultra-wideband radar has a large spectrum width (GHz level), low interception and high resolution, and can avoid interference from other systems, playing an important role in the field of target detection. The impulse-based ultra-wideband radar mainly uses a carrier-free impulse signal as the radar's transmitting signal. The radiation process of the signal by the surface radiating antenna is equivalent to the differential processing of the input time domain signal waveform, that is, the input zero-order Gaussian signal becomes a first-order Gaussian signal after passing through the antenna. Therefore, the ultra-wide spectrum ultra-narrow pulse signal appears as a bipolar impulse signal after passing through the antenna. The asymmetry and tailing effect of the bipolar impulse signal in the time domain lead to abnormal extraction of information such as the size of the target, making it difficult to effectively identify the target. In order to improve the target feature extraction and measurement performance of the ultra-wide spectrum ultra-narrow signal, it is necessary to optimize the characteristics of the bipolar signal itself and the tailing phenomenon. Summary of the invention

[0003] In view of the serious tailing effect when impulse radar adopts bipolar ultra-wide spectrum ultra-narrow pulse target detection, the present invention aims to propose a bipolar ultra-wide spectrum ultra-narrow pulse tailing suppression method based on the bipolar signal characteristics, and solve the problem of reduced target main-to-sub ratio caused by tailing based on frequency domain compensation of Hilbert transform, so as to realize the normal extraction of characteristic information such as target size, and lay a foundation for ultra-wide spectrum signal target recognition.

[0004] The ultra-wide spectrum ultra-narrow pulse signal mainly uses the impulse signal without carrier frequency as the radar transmission signal. The ideal impulse signal f(t) can be analytically expressed by Gaussian functions of different orders, which satisfies:

[0005]

[0006] The radiation process of the planar radiating antenna is equivalent to the differential processing of the input time domain signal waveform f(t), that is, the input zero-order Gaussian signal becomes a first-order Gaussian signal f'(t) after passing through the antenna, resulting in the ultra-wide spectrum and extremely narrow pulse signal to appear as a bipolar impulse signal after passing through the antenna, and its spectrum is:

[0007] F(ω)=F[f'(t)]=jω.

[0008] The Hilbert transform Fourier transform of is equivalent to F(ω) and Multiplying in the frequency domain gives:

[0009]

[0010] The final complex analysis signal The spectrum of is expressed as:

[0011]

[0012] Only the positive frequency has information, which realizes the spectrum fusion function of ultra-wide spectrum and ultra-narrow pulse signal, thereby improving the signal energy of the ultra-wide spectrum and ultra-narrow pulse waveform.

[0013] Based on the Hilbert transform processing, the waveform is compensated and corrected from the frequency domain perspective of the signal, taking into account the time-frequency characteristics of the ultra-wide spectrum and extremely narrow pulse signal.

[0014] According to the frequency domain representation of Z(ω), the effective range [0,ω 0 ], where 0≤ω'≤ω 0 Since the spectrum of the ideal impulse response f(t) is a constant with a modulus of 1, taking 1 as a reference, the system compensation of Z(ω') is as follows:

[0015] First, Z(ω') is discretized to obtain its discrete expression Z(m), m = 0, ..., M-1, where M = ω 0 / F s , F s is the sampling rate.

[0016] Secondly, the amplitude of Z(m) is fitted with a polynomial to obtain G(m), and the fitted signal is expressed as;

[0017]

[0018] Secondly, normalize and invert the fitting results to obtain P -1 (m) = 1 / P(m);

[0019] Then, considering the sidelobe suppression requirement of the time domain signal, P -1 (m) Using Gaussian window function to add window, we get:

[0020]

[0021] The Gaussian window function Where the parameter σ=0.5.

[0022] Finally, Perform IFFT transformation to obtain the final amplitude and phase corrected time domain signal:

[0023]

[0024] Wherein n=0,…,N-1, N is the length of the time domain signal.

[0025] The beneficial effects of the present invention are

[0026] The target primary-secondary ratio is increased from 10dB to over 25dB, which improves the target feature extraction and measurement performance of ultra-wide spectrum and ultra-narrow signals, laying the foundation for subsequent target identification. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 Schematic diagram of the bipolar impulse signal after passing through the antenna.

[0028] Figure 2 This is a comparison of time domain echoes before and after Hilbert transform.

[0029] Figure 3 This is the spectrum comparison diagram before and after Hilbert transform.

[0030] Figure 4 This is a spectrum comparison chart before and after frequency domain compensation.

[0031] Figure 5 This is a comparison chart of time domain echo before and after compensation. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present invention are described clearly and completely below. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0033] Take the impulse signal f(t) with a pulse width of 0.2ns recorded by a high-power microwave tube as an example. The original echo signal is as follows: Figure 1 As shown, the Gaussian rising edge and falling edge time of the ultra-wide spectrum ultra-narrow pulse echo signal are quite different, resulting in a large difference in the pulse width of the bipolar pulse signal and accompanied by a tailing signal, which will affect the target characteristic extraction and measurement of the ultra-wide spectrum ultra-narrow signal. It is necessary to carry out distance extension and tailing suppression processing of the bipolar ultra-wide spectrum ultra-narrow pulse. The Hilbert transform is used for the bipolar ultra-wideband ultra-narrow pulse echo to transform the double-sideband signal into a single-band signal. The comparison of the spectrum and time domain echo before and after the transformation is shown in the figure below. The splitting effect of the time domain signal is suppressed to a certain extent, showing a main peak state, and there is a tailing effect. The specific implementation process of tailing suppression is as follows:

[0034] Step 1: The 0.2ns time domain signal f(t) is converted into a complex signal through Hilbert transform. The time domain echo amplitude is as follows: Figure 2 As shown, the corresponding spectrum Z(ω) is further obtained. Based on the Hilbert transform processing, the signal is corrected in the frequency domain, and the comparison effect before and after the frequency domain compensation is obtained as shown in Figure 3 shown.

[0035] Step 2: According to the frequency domain representation of Z(ω), extract the effective range [0,ω 0 ] is the spectrum signal Z(ω'),

[0036] where 0≤ω′≤ω 0 .

[0037] Step 3: Discretize Z(ω') to obtain its discrete expression Z(m), m = 0, ..., M-1, where M = ω 0 / F s , F s is the sampling rate.

[0038] Step 4, perform a second-order polynomial fitting on the amplitude of Z(m) to obtain G(m), and the fitted signal is expressed as;

[0039]

[0040] Normalize and invert the fitting results to get P -1 (m) = 1 / P(m);

[0041] Step 5: Considering the sidelobe suppression requirement of the time domain signal, -1 (m) Using Gaussian window function to add window, we get:

[0042]

[0043] The Gaussian window function The parameter σ = 0.5. The spectrum after windowing is Figure 4 As shown in the figure, the signal after frequency domain correction is subjected to inverse Fourier transform to obtain the time domain echo signal. It can be seen that the long tail on the right side of the original signal is suppressed after correction, and the main-to-sub ratio of the target is also improved from about 10dB to 25dB.

[0044] Step 6, Perform IFFT transformation to obtain the final amplitude and phase corrected time domain signal:

[0045]

[0046] Where n = 0, ..., N-1, N is the length of the time domain signal. The bipolar ultra-wide spectrum time domain signal after spectrum correction is obtained as follows Figure 5As shown in the figure, the long tail on the right side of the original signal is suppressed after correction, and the main-to-sub ratio of the target is also improved from about 10dB to 25dB.

[0047] The present invention is not limited to the above specific implementations, and the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made to the above implementations based on the technical essence of the present invention shall be included in the protection scope of the present invention.

Claims

1. A bipolar ultra-wide spectrum ultra-narrow pulse tailing suppression method, characterized in that: The ultra-wide spectrum ultra-narrow pulse signal mainly uses the impulse signal without carrier frequency as the radar transmission signal. The ideal impulse signal f(t) can be analytically expressed by Gaussian functions of different orders, which satisfies: The radiation process of the planar radiating antenna is equivalent to the differential processing of the input time domain signal waveform f(t), that is, the input zero-order Gaussian signal becomes a first-order Gaussian signal f'(t) after passing through the antenna, resulting in the ultra-wide spectrum and extremely narrow pulse signal to appear as a bipolar impulse signal after passing through the antenna, and its spectrum is: F(ω)=F[f'(t)]=jω The Hilbert transform Fourier transform of is equivalent to F(ω) and Multiplying in the frequency domain gives: The final complex analysis signal The spectrum of is expressed as: It only has information on the positive frequency, realizing the spectrum fusion function of ultra-wide spectrum and ultra-narrow pulse signals, thereby improving the signal energy of ultra-wide spectrum and ultra-narrow pulse waveforms; Based on the Hilbert transform processing, the waveform is compensated and corrected from the frequency domain perspective of the signal, taking into account the time-frequency characteristics of the ultra-wide spectrum and ultra-narrow pulse signal; According to the frequency domain representation of Z(ω), the spectrum signal Z(ω') in the effective range [0,ω0] of Z(ω) is extracted, where 0≤ω'≤ω0; the system compensation of Z(ω') is performed as follows: First, Z(ω') is discretized to obtain its discrete expression Z(m), m = 0, ..., M-1, where M = ω0 / F s , F s is the sampling rate; Secondly, the amplitude of Z(m) is fitted with a polynomial to obtain G(m), and the fitted signal is expressed as; Secondly, normalize and invert the fitting results to obtain P -1 (m) = 1 / P(m); Then, considering the sidelobe suppression requirement of the time domain signal, P -1 (m) Using Gaussian window function to add window, we get: The Gaussian window function The parameter σ = 0.5; Finally, Perform IFFT transformation to obtain the final amplitude and phase corrected time domain signal: Wherein n=0,…,N-1, N is the length of the time domain signal.

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