CN105891787A - First-order sea clutter detection method based on least squares approximation - Google Patents

First-order sea clutter detection method based on least squares approximation Download PDF

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CN105891787A
CN105891787A CN201610206443.5A CN201610206443A CN105891787A CN 105891787 A CN105891787 A CN 105891787A CN 201610206443 A CN201610206443 A CN 201610206443A CN 105891787 A CN105891787 A CN 105891787A
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sea
point
bragg
frequency
suspected
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CN105891787B (en
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董英凝
赵东阳
张贺磊
邓维波
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Harbin Institute of Technology
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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
    • 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
    • G01S7/292—Extracting wanted echo-signals
    • G01S7/2923—Extracting wanted echo-signals based on data belonging to a number of consecutive radar periods
    • G01S7/2928—Random or non-synchronous interference pulse cancellers
    • 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
    • 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
    • G01S7/35—Details of non-pulse systems
    • G01S7/352—Receivers
    • G01S7/354—Extracting wanted echo-signals

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Radar Systems Or Details Thereof (AREA)

Abstract

Disclosed is a first-order sea clutter detection method based on least squares approximation. The invention relates to a first-order sea clutter detection method, and aims to solve the problem that the found Bragg peak position is inaccurate and the false alarm rate is high in the prior art. The method comprises the following steps: calculating the theoretical Bragg frequency fB based on the working frequency f0 of radar, defining a noise zone on each sea element, and calculating the threshold of each sea element; detecting sea area sea state data according to the radar, determining the maximum radial velocity Vm of ocean current, and calculating the maximum Bragg frequency offset Delta fm; determining a search scope according to Delta fm and fB, determining a suspected point of the Bragg peak, confirming the threshold of the amplitude of the suspected point, and judging whether the current sea element is effective; for the effective sea elements, taking the neighboring points of an appropriate number of suspected points to form a point set, and acquiring the approximation function of the point set using a least squares approximation method; and finally, taking the peak point of the approximation function as a Bragg peak. The first-order sea clutter detection method is applied to the field of high-frequency ground wave radar detection.

Description

First-order sea clutter detection method based on least square approximation
Technical Field
The invention relates to a first-order sea clutter detection method, and relates to the field of high-frequency ground wave radar detection.
Background
The high-frequency ground wave radar can break through the limitation of the curvature of the earth and detect the target below the sight line. Radar returns are often contaminated with a large amount of interference and noise. The first-order sea clutter of the high-frequency radar is one of the most main interferences in radar echoes, the energy of the high-frequency radar is often very high, the detection of a target is seriously influenced, and the sea clutter should be suppressed as much as possible; on the other hand, the sea clutter contains a large amount of sea state information and is a main detection object for sea state inversion. The generation mechanism of the sea clutter can be explained by the bragg resonance principle, that is, when high-frequency electromagnetic waves irradiate on a rough sea surface, the electromagnetic waves interact with the sea surface to generate a strong scattering effect, so that first-order sea clutter is generated. Theoretically, the first-order sea clutter forms a pair of energy peaks which are symmetrical about zero frequency on a frequency axis on a radar echo RD spectrum, namely Bragg peaks. The Bragg peak is very large interference to sea surface targets on existing frequency, the flooding of the targets in the frequency range is directly caused, and the Bragg peak is split and widened under the conditions of ocean current, ionospheric clutter, strong wind and the like, so that the interference range of target detection is enlarged. And abundant sea state information such as a sea surface wave field, a wind field, a flow field and the like can be obtained by measuring the deviation of the positions of the Bragg peaks, the ratio of the energy of the left Bragg peak to the energy of the right Bragg peak and the energy ratio of the first-order Bragg peak to the second-order Bragg peak. Therefore, the detection of sea clutter is the focus of research, whether the extraction of sea state information or the tracking and monitoring of sea surface targets.
The classical first-order sea clutter detection method comprises a local peak detection method, a characteristic identification-based method and the like, and the classical detection method has the common characteristic that a maximum value point in a detection range is regarded as a Bragg peak, and no processing is carried out on a spectrum near the Bragg peak. However, the coherent accumulation time is too high, which causes spectrum splitting, and the Bragg peak is split into two peaks; the spectrum near the Bragg peak has burrs due to high-frequency noise interference, and under the two conditions, the searched Bragg peak is inaccurate in position and very high in false alarm rate.
Disclosure of Invention
The invention provides a first-order sea clutter detection method based on least square approximation, which aims to solve the problems of inaccurate Bragg peak position and high false alarm rate found in the prior art.
The first-order sea clutter detection method based on least square approximation is realized according to the following steps:
the method comprises the following steps: by the operating frequency f of the radar0To find the theoretical Bragg frequency fB；
Step two: f obtained according to step oneBDefining a noise area on each sea element, and solving a threshold value of each sea element;
step three: determining the maximum value V of the ocean current radial flow velocity according to the sea state data of the sea area detected by the radarmAnd obtaining the maximum value delta f of the Bragg frequency deviationm；
Step four: according to the maximum value delta f of the Bragg frequency deviation obtained in the step threemAnd the theoretical Bragg frequency f obtained in the step oneBDetermining the search range of the Bragg peak;
step five: taking the maximum value point in the searching range determined in the step four as a suspected Bragg peak point;
step six: comparing the suspected points determined in the fifth step with the threshold obtained in the second step, if the amplitude values of the suspected points are larger than the threshold, considering that the sea metadata is valid and is valid sea yuan, and executing a seventh step; otherwise, detecting the next sea yuan;
step seven: taking a point which takes the suspected point of the Bragg peak as the center as a point set in the effective sea element determined in the step six, and solving an approximation function y;
step eight: and taking the peak point of the approximation function y obtained in the step seven as a Bragg peak point.
The invention has the following effects:
compared with the traditional detection algorithm, the method disclosed by the invention has the advantages that the approximation function of the spectrum near the Bragg peak is obtained, namely, the spectrum near the Bragg peak is smoothed, the interference caused by spectrum splitting and high-frequency noise is weakened, and the accuracy of the first-order sea clutter detection can be effectively improved.
According to the method, the approximation function of the Doppler spectrum of the high-frequency radar echo is obtained by using the least square approximation method, the spectrum near the Bragg peak is subjected to smoothing processing, the influence of interference such as spectrum splitting and high-frequency noise caused by overhigh coherent accumulation time is reduced, and the problem of inaccurate identification of the position of the Bragg peak in first-order sea clutter detection is solved.
Drawings
FIG. 1 is a range-Doppler spectrum;
FIG. 2 is a Doppler spectrum;
FIG. 3 is a graph of the result of the RD spectrum after being processed by the least square approximation method;
FIG. 4 is a graph of the results at 10km for the 4 th beam;
FIG. 5 is a graph of the results at 50km for the 4 th beam;
FIG. 6 is a graph of the results at 100km for the 4 th beam;
FIG. 7 is a graph of the results at 150km for the 4 th beam;
FIG. 8 is a flow chart of the present invention.
Detailed Description
The first embodiment is as follows: as shown in fig. 8, the first-order sea clutter detection method based on least square approximation includes the following steps:
the original radar echo data is subjected to FFT operation twice, and DBF operation once to obtain an azimuth-range-Doppler spectrum (ARD spectrum) of the echo data. The first-order sea clutter is identified by identifying the position of a first-order Bragg peak on an ARD spectrum.
The method comprises the following steps: by the operating frequency f of the radar0To find the theoretical Bragg frequency fB；
Step two: f obtained according to step oneBDefining a noise area on each sea element, and solving a threshold value of each sea element;
step three: determining the maximum value V of the ocean current radial flow velocity according to the sea state data of the sea area detected by the radarmAnd obtaining the maximum value delta f of the Bragg frequency deviationm；
Step four: according to the maximum value delta f of the Bragg frequency deviation obtained in the step threemAnd the theoretical Bragg frequency f obtained in the step oneBDetermining the search range of the Bragg peak;
step five: taking the maximum value point in the searching range determined in the step four as a suspected Bragg peak point;
step six: comparing the suspected points determined in the fifth step with the threshold obtained in the second step, if the amplitude values of the suspected points are larger than the threshold, considering that the sea metadata is valid and is valid sea yuan, and executing a seventh step; otherwise, detecting the next sea yuan;
step seven: taking a point which takes the suspected point of the Bragg peak as the center as a point set in the effective sea element determined in the step six, and solving an approximation function y;
step eight: and taking the peak point of the approximation function y obtained in the step seven as a Bragg peak point.
The algorithm is based on the least squares approximation, which is described herein.
In practical engineering applications, usually not a continuous function f (x) is obtained, but rather a discrete set of points (x) obtained from experiments or observationsi,fi) I is 0, 1. When a function value of an unspecified variable in a set of points needs to be evaluated, a numerical approximation has to be made. Is provided withIs C [ a, b ]]Upper n +1 linearly independent functions, withIs represented byThe linear subspace is formed, then for any
The least square approximation problem is to require oneMake it
Where ρ isi(i-0, 1, …, m) is a weight.
To findIs equivalent to solving a multivariate function
The normal equation of (a) is as follows:
wherein,
solving the normal equation to obtain the functionAnd function ofExist and are unique.
The second embodiment is as follows: the first difference between the present embodiment and the specific embodiment is: the above-mentionedStep one, obtaining the theoretical Bragg frequency fBThe formula of (1) is:
f B = ± 0.102 f 0 - - - ( 6 ) .
the third concrete implementation mode: the present embodiment differs from the first or second embodiment in that: the step two of obtaining the threshold value of each sea element specifically comprises the following steps:
the threshold value of each sea element is NpSum with SNR, said NpFor background noise, the SNR (given as practical) is a set minimum signal-to-noise ratio.
The algorithm sets the Doppler frequency to be [ -2fB,2fB]The area outside the range is divided into noise areas (the range of the noise areas can be adjusted according to actual conditions).
The fourth concrete implementation mode: the difference between this embodiment mode and one of the first to third embodiment modes is: obtaining the maximum value delta f of the Bragg frequency offset in the third stepmThe formula of (1) is:
empirically determining the maximum value V of the radial flow velocity of the ocean currentm(the algorithm takes 1m/s, can be adjusted according to the actual situation), and the maximum value of the frequency deviation is obtained according to the following formula:
Δf m = 2 V m λ - - - ( 7 )
wherein λ is the wavelength of the electromagnetic wave emitted by the radar.
The fifth concrete implementation mode: the difference between this embodiment and one of the first to fourth embodiments is: the specific search range for determining the bragg peak in the fourth step is as follows: [ -f ]B-Δfm～-fB+Δfm]～[fB-Δfm～fB+Δfm]。
The sixth specific implementation mode: the difference between this embodiment and one of the first to fourth embodiments is: taking a point with a suspected point of the Bragg peak as a center as a point set, and solving the approximation function y comprises the following specific processes:
taking 9-15 points with a suspected Bragg peak point as a center as a point set (the number of the point set is adjusted according to the coherent accumulation time) to solve an approximation function, and removing singular points, wherein the singular points are points with amplitude values smaller than the amplitude values of the points on the left side and the right side;
the first order Bragg peak is shaped like a parabola, so we take phi as Span {1, z, …, zn}，ρi1(i ═ 1,2, …, m); where Φ is the linear subspace, 1, z, …, znFor n +1 selected linearly independent functions, piM represents the number of points as a weight function;
determining the form of the approximation function as equation (8)
y＝ax2+bx+c (8)
Wherein x is the Doppler frequency corresponding to each point, and y is the amplitude value corresponding to each point;
solving the coefficients a, b and c by adopting the formula (9):
wherein Andfor selected linearly independent functions, xiDoppler frequency, y, corresponding to i pointiThe amplitude value corresponding to the i point; the coefficients a, b, c of the approximation function are solved by the formula (9), and the approximation function is obtained.
The first embodiment is as follows:
the data used in the experiment are derived from data collected in 2015 at 8 months of a radar experimental station of an electronic institute of Harbin Industrial university, and relevant parameters of the radar are given in Table 1.
TABLE 1 Radar System parameters
According to the relevant requirements, some parameters are not given, but are replaced by a.
The original radar echo data is subjected to two FFT operations and one DBF operation to obtain an azimuth-range-doppler spectrum (ARD spectrum) of the echo data, and a range-doppler spectrum (RD spectrum) of each beam and a doppler spectrum of each hogel can be obtained from the ARD spectrum, as shown in fig. 1 and 2. In fig. 1, two bright bands symmetrical to zero frequency are first-order sea clutter; the two peaks in fig. 2 that are symmetric about zero frequency are first order sea clutter.
Fig. 3 shows the RD pattern after least squares approximation and the found Bragg peaks are marked with purple circles. It can be seen from the figure that the purple circles basically cover two bright bands of the first-order sea clutter, which indicates that the coincidence degree of the search result and the first-order sea clutter in the original RD spectrum is very high, i.e., the positions of the left Bragg peak and the right Bragg peak are accurately found by using the method.
Fig. 4 to 7 show the doppler echo spectra after the least square approximation, in which the position of the theoretical Bragg peak is marked by a vertical line and the position of the Bragg peak is identified by a dot-dot marking algorithm. As can be seen from the figure, in different marine oceans, the algorithm accurately finds the positions of Bragg peaks, and verifies the applicability and the correctness of the algorithm. And the left side frequency offset, the right side frequency offset and the frequency offset difference of the Bragg peak are shown at the upper right part of the graph. Theoretically, the left and right frequency offsets of the Bragg peak should be equal. Therefore, the smaller the left-right frequency offset difference of the identified Bragg peak is, the better the algorithm effect is. Table 2 shows the mean and root mean square error of the left and right frequency deviations over different ranges of distances using the least squares approximation.
TABLE 2 left and right frequency deviation mean value and root mean square error table
Distance range (km) Mean value (Hz) Root mean square error (Hz)
10-50 0.0040 0.0091
50-100 0.0057 0.0112
100-150 0.0024 0.0032
150-180 0.0036 0.0060
10-100 0.0050 0.0103
100-180 0.0028 0.0044
As can be seen from table 2, the mean value and the root mean square error of the left and right frequency deviations obtained by the least square approximation method are both small, wherein the mean value of the left and right frequency deviations is controlled within 0.0057Hz, and the root mean square error of the left and right frequency deviations is controlled within 0.0112Hz, and compared with the recognition result of the traditional algorithm local peak method, the mean value of the left and right frequency deviations is improved by 9.5%, and the root mean square error of the left and right frequency deviations is improved by 1.75%. The effect of the least square approximation method is better, the accuracy of the first-order sea clutter identification result is greatly improved, and the first-order sea clutter can be accurately identified.

Claims (6)

1. The first-order sea clutter detection method based on least square approximation is characterized by comprising the following steps of:
the method comprises the following steps: by the operating frequency f of the radar0To find the theoretical Bragg frequency fB；
Step two: f obtained according to step oneBDefining a noise area on each sea element, and solving a threshold value of each sea element;
step three: determining ocean current radial flow according to sea state data of sea area detected by radarMaximum value of velocity VmAnd obtaining the maximum value delta f of the Bragg frequency deviationm；
Step four: according to the maximum value delta f of the Bragg frequency deviation obtained in the step threemAnd the theoretical Bragg frequency f obtained in the step oneBDetermining the search range of the Bragg peak;
step five: taking the maximum value point in the searching range determined in the step four as a suspected Bragg peak point;
step six: comparing the suspected points determined in the fifth step with the threshold obtained in the second step, if the amplitude values of the suspected points are larger than the threshold, considering that the sea metadata is valid and is valid sea yuan, and executing a seventh step; otherwise, detecting the next sea yuan;
step seven: taking a point which takes the suspected point of the Bragg peak as the center as a point set in the effective sea element determined in the step six, and solving an approximation function y;
step eight: and taking the peak point of the approximation function y obtained in the step seven as a Bragg peak point.
2. The method of claim 1 wherein the first order sea clutter detection based on least squares approximation is characterized by the theoretical Bragg frequency f found in step oneBThe formula of (1) is:
f B = ± 0.102 f 0 - - - ( 6 ) .
3. the method according to claim 2, wherein the threshold value for each sea element obtained in the second step is specifically:
the threshold value of each sea element is NpSum with SNR, said NpFor background noise, the SNR is a set minimum signal-to-noise ratio.
4. The method of claim 3 wherein the maximum value of the Bragg frequency offset Δ f is obtained in step threemThe formula of (1) is:
Δf m = 2 V m λ - - - ( 7 )
wherein λ is the wavelength of the electromagnetic wave emitted by the radar.
5. The method according to claim 4, wherein the step four of determining the search range of the Bragg peak specifically comprises: [ -f ]B-Δfm～-fB+Δfm]～[fB-Δfm～fB+Δfm]。
6. The method according to claim 5, wherein the point centered on the suspected point of the Bragg peak is taken as a point set in the seventh step, and the specific process of solving the approximation function y is as follows:
taking 9-15 points with a suspected Bragg peak point as a center as a point set, and removing singular points, wherein the singular points are points with amplitude values smaller than those of the points on the left side and the right side;
take Φ as Span {1, z, …, zn}，ρi1(i ═ 1,2, …, m); where Φ is the linear subspace, 1, z, …, znFor n +1 selected linearly independent functions, piM represents the number of points as a weight function;
determining the form of the approximation function as equation (8)
y＝ax2+bx+c (8)
Wherein x is the doppler frequency for each point;
solving the coefficients a, b and c by adopting the formula (9):
whereinxiDoppler frequency, y, corresponding to i pointiThe amplitude value corresponding to the i point; the coefficients a, b, c of the approximation function are solved by the formula (9), and the approximation function is obtained.
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CN113608190A (en) * 2021-07-22 2021-11-05 中国人民解放军海军航空大学航空作战勤务学院 Sea surface target detection method and system based on three characteristics of singular space
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