CN111220974A - Low-complexity frequency domain splicing method based on frequency modulation stepping pulse signals - Google Patents

Low-complexity frequency domain splicing method based on frequency modulation stepping pulse signals Download PDF

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CN111220974A
CN111220974A CN201911254097.8A CN201911254097A CN111220974A CN 111220974 A CN111220974 A CN 111220974A CN 201911254097 A CN201911254097 A CN 201911254097A CN 111220974 A CN111220974 A CN 111220974A
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CN111220974B (en
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骆雨桐
齐少宁
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Xi'an Ningyuan Electronic And Electrical Technology Co Ltd
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
    • G01S13/06—Systems determining position data of a target
    • G01S13/08—Systems for measuring distance only
    • G01S13/10—Systems for measuring distance only using transmission of interrupted, pulse modulated waves
    • G01S13/26—Systems for measuring distance only using transmission of interrupted, pulse modulated waves wherein the transmitted pulses use a frequency- or phase-modulated carrier wave
    • G01S13/28—Systems for measuring distance only using transmission of interrupted, pulse modulated waves wherein the transmitted pulses use a frequency- or phase-modulated carrier wave with time compression of received pulses
    • G01S13/282—Systems for measuring distance only using transmission of interrupted, pulse modulated waves wherein the transmitted pulses use a frequency- or phase-modulated carrier wave with time compression of received pulses using a frequency modulated carrier wave
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/66—Radar-tracking systems; Analogous systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/89—Radar or analogous systems specially adapted for specific applications for mapping or imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
    • G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
    • G01S7/28—Details of pulse systems
    • G01S7/285—Receivers

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  • Remote Sensing (AREA)
  • Radar, Positioning & Navigation (AREA)
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Abstract

The invention relates to a low-complexity frequency domain splicing method based on frequency modulation stepping pulse signals, which adopts a frequency spectrum serial connection mode to perform pulse compression on a total signal spectrum and obtains a high-resolution one-dimensional range profile through inverse Fourier transform. Compared with the existing frequency domain splicing method, the method of segmented up-sampling is adopted, and the sub-pulses are grouped and spliced in pairs, so that the computational complexity in the splicing process is reduced, the processing speed of synthesizing a broadband signal by using a frequency modulation stepping pulse signal is increased, and the real-time imaging of a tracking target by a radar is facilitated.

Description

Low-complexity frequency domain splicing method based on frequency modulation stepping pulse signals
Technical Field
The invention belongs to the field of radar signal processing, and particularly relates to a low-complexity frequency domain splicing algorithm based on frequency modulation stepping signals, which can be used for real-time high-resolution imaging and monitoring of a tracking target by a radar.
Background
The method of pulse synthesis is often used to obtain high resolution one-dimensional range profile, and the currently commonly used pulse synthesis methods include: a synthetic distance envelope method, a frequency domain splicing method and a time domain splicing method. The comparison result between the operand and the performance of the 3 algorithms is: the time domain splicing method is inferior to the other two methods in terms of both computational load and performance. The synthetic distance envelope method has the minimum computation amount, but has the problem of energy leakage, and can cause image blurring. The frequency domain splicing algorithm has the best imaging quality, but the operation amount is larger than that of a synthetic envelope method, and the engineering application still has certain limitation. Therefore, if the computation of the frequency domain splicing method can be further reduced and the processing speed of the frequency domain splicing method can be increased, the frequency domain splicing method can have more engineering practicability. Based on the point, the frequency domain splicing method is improved.
The frequency domain stitching algorithm was first proposed in 1998 to perform faster than time domain processing since no resampling of the narrowband pulses is required. However, when the spliced spectrum signal is pulse-compressed, since the spliced spectrum has a certain difference from the ideal broadband signal spectrum, it becomes difficult to construct a suitable matched filter, and the implementation process is inconvenient. In 2013, Nel, W, Tait, J, Lord, R, & Wilkinson and Tao all adopt a method of compressing a sub-pulse and then splicing frequency spectrums, and a matched filter is universal to each sub-pulse, does not need special construction, and is more convenient than a traditional algorithm. And a rapid algorithm is provided on the basis, so that the frequency domain splicing algorithm is more beneficial to engineering realization. However, in order to accurately splice, the position of the center frequency point of the sub-pulse and the position of the center frequency point in the spread spectrum need to be additionally calculated, and a position deviation may be generated in the process, so that the imaging quality is affected.
Disclosure of Invention
Technical problem to be solved
The method aims to solve the problem of difficulty in real-time imaging caused by large data volume under the requirement of high-resolution imaging. The invention provides a low-complexity frequency domain splicing method based on frequency modulation stepping pulse signals, which adopts a frequency spectrum serial connection mode to perform pulse compression on a total signal spectrum and obtains a high-resolution one-dimensional range profile through inverse Fourier transform.
Technical scheme
A low-complexity frequency domain splicing method based on frequency modulation stepping pulse signals is characterized by comprising the following steps:
step 1: echo sub-pulse frequency domain matched filtering
Performing frequency mixing processing on echoes received by a radar to obtain a baseband signal, wherein the sampling rate is set to fs, and the number of sub-pulse sampling points is set to M; and (3) performing inverse Fourier transform on each sub-pulse baseband echo, namely performing M-point FFT to obtain a corresponding signal spectrum:
Figure BDA0002309823150000021
wherein i represents the ith sub-pulse, N represents N sub-pulses in a group of frequency modulation stepping pulse signals, and BsRepresenting the sub-pulse bandwidth, f0Representing the carrier frequency, af the frequency step, tau the target delay,
Figure BDA0002309823150000022
representing the chirp rate, TpIs the sub-pulse time width, t0For the gate delay, rect (-) is a rectangular pulse function,
Figure BDA0002309823150000023
indicates a width of TpThe rectangular pulse of (2);
and performing frequency domain matched filtering on each sub-pulse echo signal, wherein the frequency spectrum of the ideal matched filter is as follows:
Figure BDA0002309823150000024
the result of matched filtering is:
Figure BDA0002309823150000025
step 2: multiplying the matched and filtered signal by a gate delay factor to correct the phase error, wherein the gate delay factor is as follows: exp [ j2 pi (f)0+iΔf)t0]；
Figure BDA0002309823150000031
And step 3: zero-filling up-sampling is carried out on the corrected sub-pulse frequency spectrum, so that the number of sampling points is enlarged to 2 times of the original number;
and 4, step 4: carrying out spectrum shifting on the spread spectrum, converting the IFFT of the spread spectrum into a time domain, multiplying the time-shifting factor by the IFFT, shifting the spectrum to a corresponding position, and then carrying out FFT (fast Fourier transform) conversion to a frequency domain;
and 5: adjacent two shifted frequency domains are combined into a group by superposition, and whether only one group of frequency spectrums exists after superposition is judged; if not, repeating the steps 2-5 until the superposition result has only one group of frequency spectrums, namely the required spliced total spectrum;
step 6: and performing IFFT on the finally superposed spliced total spectrum to obtain a high-resolution one-dimensional range profile.
The time shift factor in step (4) is a (i, t) ═ exp (j2 pi m Δ ft),
Figure BDA0002309823150000032
advantageous effects
Compared with the existing frequency domain splicing algorithm, the low-complexity frequency modulation stepping pulse signal-based frequency domain splicing method adopts a segmented up-sampling method to splice sub-pulses in pairs and groups, thereby reducing the computational complexity in the splicing process, improving the processing speed of synthesizing a broadband signal by using the frequency modulation stepping pulse signal, and being beneficial to real-time imaging of a tracking target by a radar.
Drawings
FIG. 1 is a flow chart of the algorithm implementation of the present invention
FIG. 2 is a diagram of a scattering point model of an object
FIG. 3 is a graph of single sub-pulse imaging results
FIG. 4 is a simulation diagram of a conventional frequency domain splicing algorithm
FIG. 5 is a simulation diagram of an improved frequency domain stitching algorithm
FIG. 6 is a complexity contrast plot
Detailed Description
The invention will now be further described with reference to the following examples and drawings:
referring to fig. 1, the specific implementation steps of this example are as follows:
step 1, echo sub-pulse frequency domain matching filtering
The echoes received by the radar can be expressed as:
Figure BDA0002309823150000041
i represents the ith sub-pulse, N represents N sub-pulses in a group of frequency modulated step pulse signals, f0Represents the carrier frequency,. DELTA.f represents the frequency step, τ represents the target time delay, and k represents the chirp rate
Figure BDA0002309823150000042
TpIs the sub-pulse time width, TrRepresenting the sub-pulse repetition time, rect (-) is a rectangular pulse function,
Figure BDA0002309823150000043
mixing the echo and the local oscillator signal to obtain a baseband signal, wherein the expression of the ith sub-pulse after mixing is as follows:
Figure BDA0002309823150000044
performing frequency mixing processing on echoes received by a radar to obtain a baseband signal, wherein the sampling rate is set to fs, and the number of sub-pulse sampling points is set to M (M is 2)q). And (3) performing inverse Fourier transform on each sub-pulse baseband echo, namely performing M-point FFT to obtain a corresponding signal spectrum:
Figure BDA0002309823150000045
i represents the ith sub-pulse, N represents N sub-pulses in a group of frequency modulation stepping pulse signals, BsRepresenting the sub-pulse bandwidth, f0Represents the carrier frequency,. DELTA.f represents the frequency step, τ represents the target time delay, and k represents the chirp rate
Figure BDA0002309823150000046
TpIs the sub-pulse time width, rect (-) is a rectangular pulse function,
Figure BDA0002309823150000047
indicates a width of TpThe square pulse of (2).
And performing frequency domain matched filtering on each sub-pulse echo signal, wherein the frequency spectrum of the ideal matched filter is as follows:
Figure BDA0002309823150000051
the result of matched filtering is:
Figure BDA0002309823150000052
and 2, multiplying the matched and filtered signal by a gate delay factor to correct the phase error. The gate delay factor is: exp [ j2 pi (f)0+iΔf)t0]，
Figure BDA0002309823150000053
And 3, carrying out zero filling and up-sampling on the corrected sub-pulse frequency spectrum, so that the number of sampling points is enlarged to 2 times of the original number.
And 4, carrying out spectrum shifting on the expanded spectrum. And after the spectrum after being spread is IFFT converted into a time domain, the time shift factor is multiplied, the spectrum is moved to a corresponding position, and then FFT is converted into a frequency domain. Constructing a time shift factor according to the carrier frequency of the sub-pulse: a (i, t) ═ exp (j2 pi m Δ ft),
Figure BDA0002309823150000054
and 5, overlapping and synthesizing adjacent shifted frequency domains into a group, and judging whether only one group of frequency spectrums exists after overlapping. If not, repeating the steps (2) to (5) until the superposition result has only one group of frequency spectrums, namely the required spliced total spectrum.
And 6, performing IFFT on the finally superposed spliced total spectrum to obtain a high-resolution one-dimensional range profile.
The effects of the invention can be further illustrated by simulation:
1. simulation conditions
The simulation was implemented using MATLAB R2015b software, and the number of sub-pulses in a group of pulse trains was set to 32, and the sub-pulse bandwidth was set to 60M. The sub-pulse time width was 40. mu.s, and the pulse repetition time was 300. mu.s. The longitudinal distances of scattering points on the target relative to the geometric center of the target are set to be three, namely 100m, 100.09m and 103 m. The resolution of the single sub-pulse is 2.5m, and the resolution of the processed composite pulse is 0.078 m.
2. Emulated content and results
The three scattering point models are shown in fig. 2, the imaging result of a single sub-pulse is shown in fig. 3, the simulation result of the traditional frequency domain stitching algorithm is shown in fig. 4, and the simulation result of the improved frequency domain stitching algorithm is shown in fig. 5. As can be seen from a comparison of fig. 2 and fig. 3, the single sub-pulse cannot distinguish between the two targets 100m and 100.09m, and can be distinguished after synthesis. As can be seen from comparison of fig. 4 and 5, the improved method achieves the same high resolution effect as the conventional method. Fig. 6 shows that the improved algorithm has lower computational complexity and higher computational efficiency, so the improved algorithm is superior to the traditional algorithm.

Claims (2)

1. A low-complexity frequency domain splicing method based on frequency modulation stepping pulse signals is characterized by comprising the following steps:
step 1: echo sub-pulse frequency domain matched filtering
Performing frequency mixing processing on echoes received by a radar to obtain a baseband signal, wherein the sampling rate is set to fs, and the number of sub-pulse sampling points is set to M; and (3) performing inverse Fourier transform on each sub-pulse baseband echo, namely performing M-point FFT to obtain a corresponding signal spectrum:
Figure FDA0002309823140000011
wherein i represents the ith sub-pulse, N represents N sub-pulses in a group of frequency modulation stepping pulse signals, and BsRepresenting the sub-pulse bandwidth, f0Represents the carrier frequency,. DELTA.f represents the frequency step size,. tau represents the eyeThe time delay is marked by a time delay mark,
Figure FDA0002309823140000012
representing the chirp rate, TpIs the sub-pulse time width, t0For the gate delay, rect (-) is a rectangular pulse function,
Figure FDA0002309823140000013
indicates a width of TpThe rectangular pulse of (2);
and performing frequency domain matched filtering on each sub-pulse echo signal, wherein the frequency spectrum of the ideal matched filter is as follows:
Figure FDA0002309823140000014
the result of matched filtering is:
Figure FDA0002309823140000015
step 2: multiplying the matched and filtered signal by a gate delay factor to correct the phase error, wherein the gate delay factor is as follows: exp [ j2 pi (f)0+iΔf)t0]；
Figure FDA0002309823140000016
And step 3: zero-filling up-sampling is carried out on the corrected sub-pulse frequency spectrum, so that the number of sampling points is enlarged to 2 times of the original number;
and 4, step 4: carrying out spectrum shifting on the spread spectrum, converting the IFFT of the spread spectrum into a time domain, multiplying the time-shifting factor by the IFFT, shifting the spectrum to a corresponding position, and then carrying out FFT (fast Fourier transform) conversion to a frequency domain;
and 5: adjacent two shifted frequency domains are combined into a group by superposition, and whether only one group of frequency spectrums exists after superposition is judged; if not, repeating the steps 2-5 until the superposition result has only one group of frequency spectrums, namely the required spliced total spectrum;
step 6: and performing IFFT on the finally superposed spliced total spectrum to obtain a high-resolution one-dimensional range profile.
2. A low complexity frequency domain concatenation algorithm based on FM stepped pulse signals according to claim 1, wherein said time shift factor in step (4) is A (i, t) ═ exp (j2 π m Δ ft),
Figure FDA0002309823140000021
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