CN113640763B - Method for estimating distribution shape parameters of sea clutter amplitude of lognormal texture based on fractional order moment - Google Patents

Method for estimating distribution shape parameters of sea clutter amplitude of lognormal texture based on fractional order moment Download PDF

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CN113640763B
CN113640763B CN202110865345.3A CN202110865345A CN113640763B CN 113640763 B CN113640763 B CN 113640763B CN 202110865345 A CN202110865345 A CN 202110865345A CN 113640763 B CN113640763 B CN 113640763B
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sea clutter
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CN113640763A (en
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薛健
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Xian University of Posts and Telecommunications
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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
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/418—Theoretical aspects
    • 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
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

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

Abstract

The invention relates to the technical field of radar signal processing, in particular to a method for estimating a shape parameter of a lognormal texture sea clutter amplitude distribution based on fractional order moment, which adopts a negative fractional order moment and a positive fractional order moment of sea clutter sample amplitude, compared with the existing estimation method based on zlogz and the estimation method based on high order moment, the estimation accuracy of the shape parameter is improved while the calculation complexity is reduced, and further, the estimation value of the shape parameter of the lognormal texture sea clutter amplitude distribution obtained by the method is improvedThe method is applied to the radar target detection method obtained in the radar target detection method, and the value of the test statistic is more accurate, so that the detection performance of the radar target is further improved.

Description

Method for estimating distribution shape parameters of sea clutter amplitude of lognormal texture based on fractional order moment
Technical Field
The invention relates to the technical field of radar signal processing, in particular to a method for estimating a lognormal texture sea clutter amplitude distribution shape parameter based on fractional order moment.
Background
Sea-going radars are operated so as to inevitably receive back-scattered signals of sea-going electromagnetic waves emitted by the radar, which are often referred to as sea clutter. The radar target detection method in the background of the sea clutter is generally related to the shape parameter of the sea clutter amplitude distribution, so in order to better detect radar targets, the shape parameter of the sea clutter amplitude distribution must be accurately estimated. The sea clutter can be modeled using a gaussian model when the radar resolution unit length is much greater than the wavelength of the swell or the radar observation ground angle is greater than 10 degrees. However, as radar resolution increases or the observed ground clearance decreases, sea clutter may appear significantly non-gaussian, and the gaussian model may be severely mismatched. The current model capable of effectively modeling the non-Gaussian sea clutter is a composite Gaussian model, and the model is based on a sea clutter physical formation mechanism and subjected to theoretical verification and experimental verification. The composite gaussian model describes sea clutter using the product of a slowly varying texture component and a rapidly varying speckle component. The speckle component of sea clutter is the electromagnetic wave speckle component caused by small scale capillary waves at the sea surface, which is a complex gaussian random variable subject to zero mean unit power. The texture component of the sea clutter is generated by large-scale gravitational waves of the sea clutter, and the texture component is a random variable. The amplitude characteristics of the composite gaussian sea clutter are determined by the probability density function of the texture component. Under the composite Gaussian model, according to probability density functions of texture components and speckle components, the amplitude distribution of sea clutter can be obtained based on a full probability formula. The texture component of the sea clutter is modeled as a random variable conforming to the gamma distribution, so that K distribution describing the amplitude of the sea clutter widely used in the radar target detection field can be obtained. However, with the increase of radar resolution, the K-profile has not been able to accurately describe non-gaussian sea clutter. In order to model the amplitude of non-gaussian sea clutter more accurately, a lognormal texture composite gaussian distribution is proposed. The lognormal texture composite gaussian distribution models the texture component of the sea clutter with a lognormal distribution, which is more suitable than the K distribution for describing the amplitude characteristics of the non-gaussian sea clutter.
The shape parameters contained in the lognormal texture composite gaussian distribution control the non-gaussian nature of the sea clutter: the larger the shape parameter, the more severe the non-gaussian nature of the sea clutter; the smaller the shape parameter, the weaker the non-gaussian nature of the sea clutter. The shape parameter occurs in the radar target detection method in the context of lognormal texture sea clutter, so the shape parameter must be estimated using sea clutter data received by the radar prior to detecting a target. There are currently high order moment estimation methods and zlogz methods for estimation methods of lognormal texture sea clutter amplitude distribution shape parameters, which are described in the literature, "i.chalabi and a.mezache, estimators of compound Gaussian clutter with log-normal texture, remote Sensing Letters, vol.10, no.7, pp.709-716, jul.2019, doi:10.1080/2150704x.2019.1601275", in which it is pointed out that the zlogz-based method performs better than the high order moment-based estimation method for lognormal texture sea clutter amplitude distribution shape parameter estimation. However, when the sea clutter is serious in non-Gaussian property (namely, when the shape parameter is large), the estimation error of the zlogz-based estimation method for the distribution shape parameter of the amplitude of the sea clutter with the lognormal texture is overlarge, and the detection performance of the radar target under the background of the sea clutter with the lognormal texture is affected.
Disclosure of Invention
The invention aims to solve the technical problems that the existing method for estimating the shape parameters of the amplitude distribution of the sea clutter in the lognormal texture has insufficient precision, and provides a method for estimating the shape parameters of the amplitude distribution of the sea clutter in the lognormal texture based on fractional order moment aiming at the defects in the prior art so as to improve the estimation precision of the shape parameters in the amplitude distribution of the sea clutter in the lognormal texture.
The technical problems solved by the invention can be realized by adopting the following technical scheme:
the method for estimating the distribution shape parameter of the amplitude of the sea clutter with the lognormal texture based on fractional order moment comprises the following steps of
S1: n-order theoretical moment m for calculating amplitude distribution of sea clutter with lognormal texture n Wherein m represents a theoretical moment of the sea clutter amplitude distribution, and n represents an order of the sea clutter amplitude distribution moment;
s2: according to the n-order theoretical moment m obtained in S1 n Deriving a mathematical equation of a lognormal texture sea clutter amplitude distribution shape parameter gamma based on fractional order moment;
s3: n sea clutter amplitude samples are selected from sea clutter data received by a radar, and statistical moments of the N sea clutter amplitude samples based on fractional order are calculated respectively;
s4: substituting the fractional order statistical moment obtained in the step S3 into the mathematical equation in the step S2 to obtain the estimated value of the lognormal texture sea clutter amplitude distribution shape parameter based on the fractional order moment
S5: according to the obtained lognormal texture sea clutter amplitude distribution shape parameter estimation value based on fractional order momentThe parameter estimation value is applied to a radar target detection method under the background of the lognormal texture sea clutter, and the detection statistic of the radar target detection method is calculated and used for improving the detection performance of the radar target.
Further, the step S2 is based onThe mathematical equation of the lognormal texture sea clutter amplitude distribution shape parameter gamma of fractional order moment is derivedAnd->Mathematical equations for the log-normal texture sea clutter amplitude distribution shape parameter gamma.
Further, in the step S3, the calculation of the N sea clutter amplitude samples based on the fractional order statistical moment is based on the calculation of the N sea clutter amplitude samplesStep sum->Statistical moment of order->And->
Further, the S1 calculates an n-order theoretical moment m of the logarithmic normal texture sea clutter amplitude distribution n The method also comprises the following steps:
s01: the lognormal texture sea clutter amplitude distribution probability density function f (r) is calculated, and the calculation formula is as follows:
wherein r represents the amplitude of the sea clutter, τ represents the texture component of the sea clutter, γ represents the shape parameter of the amplitude distribution of the sea clutter with lognormal texture, δ represents the scale parameter of the amplitude distribution of the sea clutter with lognormal texture, ln (·) represents the natural logarithmic function; e, e (·) Representing a natural exponential function;
s02: according to S01, calculating an n-order theoretical moment m of the amplitude distribution of the lognormal texture sea clutter, wherein the lognormal texture sea clutter amplitude distribution probability density function f (r) is obtained in the step 1 n The calculation formula is as follows:
wherein E (·) represents a statistical average and Γ (·) represents a gamma function.
Further, deriving the fractional order moment based in the step S2And->The mathematical equation of the logarithmic normal texture sea clutter amplitude distribution shape parameter gamma comprises the following steps:
s001: n-order theoretical moment m using lognormal texture sea clutter amplitude distribution n ObtainingThe equation for the moment is as follows:
s002: n-order theoretical moment m using lognormal texture sea clutter amplitude distribution n ObtainingThe equation for the moment is as follows:
s003: solving a mathematical equation of a lognormal texture sea clutter amplitude distribution shape parameter gamma based on fractional order moment by using the equations in S001 and S002, wherein the mathematical equation is as follows:
further, the N sea clutter amplitude samples in the S3 are r 1 ,r 2 ,...,r N Respectively calculating N sea clutter amplitude samples r 1 ,r 2 ,...,r N A kind of electronic deviceStep sum->Statistical moment of order->And->Where N represents the number of sea clutter samples and r represents the amplitude of sea clutter; the calculation formula is as follows:
further, the order in S4The value of (2) is +.>The value of (2) is +.>Will->And->Substituting into the mathematical equation in S2 to obtain the estimation value of the lognormal texture sea clutter amplitude distribution shape parameter based on fractional order momentThe formula is as follows:
the beneficial effects of the invention are as follows:
compared with the prior art, the method for estimating the shape parameter of the lognormal texture sea clutter amplitude distribution based on the fractional moment adopts the negative fractional moment and the positive fractional moment of the sea clutter sample amplitude, reduces the calculation complexity and improves the estimation precision of the shape parameter compared with the existing estimation method based on zlogz and the estimation method based on the high-order moment, and further obtains the shape parameter estimation value of the lognormal texture sea clutter amplitude distribution by the methodThe method is applied to the radar target detection method obtained in the radar target detection method, and the value of the test statistic is more accurate, so that the detection performance of the radar target is further improved.
Drawings
The invention will be further described with reference to the drawings and examples.
FIG. 1 is a schematic flow chart of an implementation of the present invention.
FIG. 2 is a graph showing the relative root mean square error of the log-normal texture sea clutter amplitude distribution shape parameter estimation obtained by the present invention and the prior art method.
Detailed Description
The scheme of the estimation method of the lognormal texture sea clutter amplitude distribution shape parameter based on fractional order moment provided by the invention will be described in detail by several specific embodiments.
It is first to be noted that the same symbols are used for the same meaning in all the formulae of the present invention.
Wherein m represents the theoretical moment of sea clutter amplitude distribution;
n represents the order of the sea clutter amplitude distribution moment;
r represents the amplitude of sea clutter;
tau represents the texture component of the sea clutter;
gamma represents the shape parameter of the lognormal texture sea clutter amplitude distribution;
delta represents a scale parameter of the lognormal texture sea clutter amplitude distribution.
Referring to FIG. 1, the invention is a method for estimating the distribution shape parameter of the amplitude of sea clutter with a lognormal texture based on fractional order moment, comprising the following steps
S1: n-order theoretical moment m for calculating amplitude distribution of sea clutter with lognormal texture n ；
The n-order theoretical moment m of the amplitude distribution of the sea clutter with the log-normal texture is calculated n The method specifically comprises the following steps:
s01: according to a probability density function of lognormal distribution obeyed by a texture component tau of the sea clutter and a probability density function of conditional Rayleigh distribution obeyed by a sea clutter amplitude r, a lognormal texture sea clutter amplitude distribution probability density function f (r) is calculated, and a calculation formula is as follows:
wherein ln (·) represents a natural logarithmic function; e, e (·) Representing a natural exponential function;
s02: according to the lognormal texture sea clutter amplitude distribution probability density function f (r) obtained in S01, calculating an n-order theoretical moment m of lognormal texture sea clutter amplitude distribution n The calculation formula is as follows:
wherein E (·) represents a statistical average and Γ (·) represents a gamma function;
s2: according to the n-order theoretical moment m obtained in S1 n Deriving a mathematical equation of a lognormal texture sea clutter amplitude distribution shape parameter gamma based on fractional order moment;
further, the mathematical equation of the distribution shape parameter gamma of the sea clutter amplitude of the lognormal texture based on the fractional order moment in S2 is derivedAnd->Mathematical equation of the logarithmic normal texture sea clutter amplitude distribution shape parameter gamma;
further, deriveAnd->The mathematical equation of the logarithmic normal texture sea clutter amplitude distribution shape parameter gamma comprises the following steps:
s001: n-order theoretical moment m using lognormal texture sea clutter amplitude distribution n ObtainingThe equation for the moment is as follows:
s002: n-order theoretical moment m using lognormal texture sea clutter amplitude distribution n ObtainingThe equation for the moment is as follows:
s003: solving a mathematical equation of a lognormal texture sea clutter amplitude distribution shape parameter gamma based on fractional order moment by using the equations in S001 and S002, wherein the mathematical equation is as follows:
s3: n sea clutter amplitude samples are selected from sea clutter data received by a radar, and statistical moments of the N sea clutter amplitude samples based on fractional order are calculated respectively;
further, N sea clutter amplitude samples in S3 are r 1 ,r 2 ,...,r N 。
Further, N sea clutter amplitude samples r are respectively selected from the sea clutter data received from the radar 1 ,r 2 ,...,r N The acquisition method comprises the following steps:
a1, the radar transmits pulse signals to the sea surface, echo data received by the radar is represented as a three-dimensional matrix Z, wherein Z is a P multiplied by L multiplied by Q three-dimensional matrix, P represents the azimuth number of the echo data matrix, L represents the distance unit number of the echo data matrix, and Q represents the pulse number of the echo data matrix;
a2, selecting a sea clutter data region G from an echo data matrix Z, wherein G is a three-dimensional matrix of P multiplied by L multiplied by Q, P is more than or equal to 1 and less than or equal to P, L is more than or equal to 1 and less than or equal to L, and the amplitude of sea clutter data contained in G is expressed as r 1 ,r 2 ,...,r N ，N＝p×l×Q；
A3, respectively calculating N sea clutter amplitude samples r 1 ,r 2 ,...,r N A kind of electronic deviceStep sum->Statistical moment of order->Andwhere N represents the number of sea clutter samples and r represents the amplitude of sea clutter;
the formula is as follows:
s4: substituting the fractional order statistical moment obtained in the step S3 into the mathematical equation in the step S2 to obtain the estimated value of the lognormal texture sea clutter amplitude distribution shape parameter based on the fractional order moment
Further, in S4 is a commandThe value of (2) is +.>The value of (2) is +.>Will->And->Substituting the mathematical equation about the shape parameter γ substituted into S2, equation 5, to obtain the estimated value ++of the shape parameter of the lognormal texture sea clutter amplitude distribution based on the fractional order moment>The formula is as follows:
s5: according to the obtained lognormal texture sea clutter amplitude distribution shape parameter estimation value based on fractional order momentThe parameter estimation value is applied to a radar target detection method under the background of the lognormal texture sea clutter, and the detection statistic of the radar target detection method is calculated and used for improving the detection performance of the radar target.
The radar target detection method comprises the following steps:
wherein α represents a test statistic of the radar target detection method, and M represents a cumulative number of coherent pulses,/-for the radar target detection method>Estimated value representing sea clutter texture without target,/->An estimated value, q, representing sea clutter texture in the presence of a target 0 Indicating the power after radar echo whitening without target,/->The power after sea clutter whitening under the condition of a target is represented, gamma represents the shape parameter of the amplitude distribution of the sea clutter with the lognormal texture, and delta represents the scale parameter of the amplitude distribution of the sea clutter with the lognormal texture;
the obtained lognormal texture sea clutter amplitude distribution shape parameter estimation value based on fractional order momentAnd carrying out the equation to obtain the test statistic of the radar target detection method, wherein the test statistic is obtained by the methodThe estimated value of the logarithmic normal texture sea clutter amplitude distribution shape parameter obtained by the explicit method>The detection statistics obtained in the radar target detection method are more accurate, so that the detection performance of radar targets is further improved.
The effects of the present invention will be further described with reference to simulation experiments.
1. Simulation parameters
And simulating the sea clutter amplitude samples with the lognormal texture by using matlab software, namely selecting N sea clutter amplitude samples, setting experimental simulation parameters to be the number of samples N=10000, setting scale parameters delta=1, increasing the shape parameters gamma from 0.1 to 10, and taking the increasing step length to 0.1. The number of independent simulation experiments for each shape parameter was set to 10000. Estimating the error of the shape parameter estimate using a relative root mean square error (Relative Root Mean Square Error, RRMSE), the calculation formula of RRMSE being
2. Simulation experiment contents
In the simulation experiment, the shape parameters of sea clutter data are estimated by using a high-order moment estimation method, a zlogz estimation method and the estimation method of the invention respectively, and an RRMSE graph of an estimation result is drawn.
The experimental result is shown in fig. 2, wherein the horizontal axis represents the real shape parameter gamma of the sea clutter data, and the vertical axis represents the RRMSE corresponding to the estimation result. In fig. 2, the "·" marked curve represents the RRMSE curve corresponding to the high-order moment estimation method, the "- -" marked curve represents the RRMSE curve corresponding to the zlogz estimation method, and the "-" marked curve represents the RRMSE curve corresponding to the present invention.
As can be seen from fig. 2, the RRMSE of the present invention is smaller than the high order moment estimation method and the zlogz estimation method when the shape parameter is greater than 2.5. The larger the shape parameter, the stronger the non-gaussian property of the sea clutter, and the result of fig. 2 shows that the estimation error of the shape parameter is smaller than that of the prior method under the non-gaussian sea clutter environment.
In summary, the invention provides a lognormal texture sea clutter amplitude distribution shape parameter estimation method based on fractional order moment, and the method has high estimation precision on shape parameters under the background of non-Gaussian sea clutter.
Therefore, the obtained log normal texture sea clutter amplitude distribution shape parameter estimation value with high estimation precision is adoptedThe method is applied to radar target detection under the background of the lognormal texture sea clutter, and improves the detection performance of radar targets.
The embodiments of the present invention have been described in detail with reference to the drawings, but the present invention is not limited to the above embodiments, and various changes can be made within the scope of the knowledge of those skilled in the art without departing from the spirit of the present invention, which is within the scope of the present invention.
The technical solutions between the embodiments may be combined with each other, but it is necessary to base the implementation on the basis of those skilled in the art that when the combination of technical solutions contradicts or cannot be implemented, it should be considered that the combination of technical solutions does not exist and is not within the scope of protection claimed by the present invention.

Claims (7)

1. The estimation method of the lognormal texture sea clutter amplitude distribution shape parameter based on fractional order moment is characterized by comprising the following steps of: comprising the following steps
S1: n-order theoretical moment m for calculating amplitude distribution of sea clutter with lognormal texture n The calculation formula is as follows:
wherein m represents the theoretical moment of the sea clutter amplitude distribution, n represents the order of the sea clutter amplitude distribution moment, E (·) represents statistical averaging, Γ (·) represents a gamma function;
s2: according to the n-order theoretical moment m obtained in S1 n The mathematical equation of the lognormal texture sea clutter amplitude distribution shape parameter gamma based on the fractional order moment is deduced as follows:
wherein the method comprises the steps ofIs->Theoretical moment of time order m n Value of->Is->Theoretical moment of time order m n Is a value of (2);
s3: n sea clutter amplitude samples are selected from sea clutter data received by a radar, statistical moment based on fractional order of the N sea clutter amplitude samples is calculated respectively, and the statistical moment is calculated based on the N sea clutter amplitude samples respectivelyStep sum->Statistical moment of order->And->The calculation formula is as follows:
where N represents the number of sea clutter samples and r represents the amplitude of sea clutter;
s4: substituting the fractional order statistical moment obtained in the step S3 into the mathematical equation in the step S2 to obtain the estimated value of the lognormal texture sea clutter amplitude distribution shape parameter based on the fractional order momentThe formula is as follows:
s5: according to the obtained lognormal texture sea clutter amplitude distribution shape parameter estimation value based on fractional order momentThe parameter estimation value is applied to a radar target detection method under the background of the lognormal texture sea clutter, and the detection statistic of the radar target detection method is calculated and used for improving the detection performance of the radar target.
2. The estimation method of the lognormal texture sea clutter amplitude distribution shape parameter based on fractional order moment according to claim 1, wherein the estimation method is characterized in that: the mathematical equation of the S2 based on the lognormal texture sea clutter amplitude distribution shape parameter gamma of the fractional order moment is derivedAnd->Mathematical equations for the log-normal texture sea clutter amplitude distribution shape parameter gamma.
3. The estimation method of the lognormal texture sea clutter amplitude distribution shape parameter based on the fractional moment according to claim 2, wherein the estimation method is characterized in that: the step S3 of calculating N sea clutter amplitude samples based on fractional order is based on the calculated N sea clutter amplitude samplesStep sum->Statistical moment of order->And->
4. The estimation method of the lognormal texture sea clutter amplitude distribution shape parameter based on fractional order moment according to claim 1, wherein the estimation method is characterized in that: the n-order theoretical moment m of the logarithmic normal texture sea clutter amplitude distribution is calculated in the S1 n The method also comprises the following steps:
s01: the lognormal texture sea clutter amplitude distribution probability density function f (r) is calculated, and the calculation formula is as follows:
wherein r represents the amplitude of the sea clutter, τ represents the texture component of the sea clutter, γ represents the shape parameter of the amplitude distribution of the sea clutter with lognormal texture, δ represents the scale parameter of the amplitude distribution of the sea clutter with lognormal texture, ln (·) represents the natural logarithmic function; e, e (·) Representing a natural exponential function;
s02: calculating logarithm according to the logarithmic normal texture sea clutter amplitude distribution probability density function f (r) obtained in S01N-order theoretical moment m of normal texture sea clutter amplitude distribution n The calculation formula is as follows:
wherein E (·) represents a statistical average and Γ (·) represents a gamma function.
5. The estimation method of the lognormal texture sea clutter amplitude distribution shape parameter based on the fractional moment according to claim 2, wherein the estimation method is characterized in that: the S2 derives a fractional order momentAnd->The mathematical equation of the logarithmic normal texture sea clutter amplitude distribution shape parameter gamma comprises the following steps:
s001: n-order theoretical moment m using lognormal texture sea clutter amplitude distribution n ObtainingThe equation for the moment is as follows:
s002: n-order theoretical moment m using lognormal texture sea clutter amplitude distribution n ObtainingThe equation for the moment is as follows:
s003: solving a mathematical equation of a lognormal texture sea clutter amplitude distribution shape parameter gamma based on fractional order moment by using the equations in S001 and S002, wherein the mathematical equation is as follows:
6. the estimation method for the distribution shape parameter of the amplitude of the sea clutter based on the lognormal texture of fractional order moment according to claim 3, wherein the estimation method is characterized in that: the N sea clutter amplitude samples in the S3 are r 1 ,r 2 ,...,r N Respectively calculating N sea clutter amplitude samples r 1 ,r 2 ,...,r N A kind of electronic deviceStep sum->Statistical moment of order->And->Where N represents the number of sea clutter samples and r represents the amplitude of sea clutter; the calculation formula is as follows:
7. the estimation method for the distribution shape parameter of the amplitude of the sea clutter based on the lognormal texture of fractional order moment according to claim 3, wherein the estimation method is characterized in that: the S4 is a commandThe value of (2) is +.>The value of (2) is +.>Will->And->Substituting into the mathematical equation in S2 to obtain the estimation value of the lognormal texture sea clutter amplitude distribution shape parameter based on fractional order momentThe formula is as follows:
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