CN116973876B - Forward scattering radar moving target detection method and device based on gradient test - Google Patents
Forward scattering radar moving target detection method and device based on gradient test Download PDFInfo
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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
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- G01S7/415—Identification of targets based on measurements of movement associated with the target
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Abstract
The application discloses a forward scattering radar moving target detection method and device based on gradient test, wherein the method comprises the following steps: the problem of judging whether the echo signal received by the forward scattering radar contains the target signal is expressed as binary hypothesis test; calculating probability density functions of echo signals under two assumptions; setting an expression of a complex parameter gradient test; calculating the maximum likelihood estimation value of the complex amplitude of the target signal under the assumption that the target exists and the maximum likelihood estimation value of the complex amplitude of the target signal under the assumption that the target does not exist, the complex amplitude of the direct wave signal and the variance of the noise, substituting the maximum likelihood estimation value into an expression of complex parameter gradient test to obtain gradient test statistics, comparing the gradient test statistics with a set threshold, judging that the echo signal contains the target signal if the gradient test statistics are larger than the threshold, and otherwise judging that the echo signal does not contain the target signal. The application can effectively improve the detection performance of the forward scattering radar on the moving target.
Description
Technical Field
The application belongs to the technical field of radar signal processing, and particularly relates to a forward scattering radar moving target detection method and device based on gradient test, computer equipment and a computer readable storage medium.
Background
The stealth technology takes the radar scattering cross section area reduction as a main target, and is one of four threats of modern radars. In recent years, forward scattering radar has gained widespread attention in detecting stealth targets and small targets. This is due to the close bistatic angle of forward scattering radarThe radar receiver is now operating in the forward scattering region of the target, where the radar cross-sectional area of the target is typically increased by a few tens of dB to a few tens of dB compared to a single-base radar. Therefore, forward scattering radar has an incomparable advantage over single-base radar in terms of target detection. The forward scattering radar is widely applied to the fields of air target detection, ground and sea surface target detection and the like.
As the prior art, CN102338870B discloses a three-dimensional target tracking method using forward scattering radar, and CN115015863a discloses a uniform motion target parameter estimation method based on forward scattering radar network.
In addition to noise, the echo signals received by the receiver of the forward scatter radar also include direct wave signals. The conventional method suppresses the direct wave signal by designing a narrow-band high-pass filter to project the output of the square detector into a subspace perpendicular to the direct wave signal. And then the signal after the direct wave signal is restrained is passed through a matched filter to implement target detection. However, experimental results show that the conventional method has a larger detection performance loss compared to the ideal detector.
Disclosure of Invention
The application aims to provide a forward scattering radar moving target detection method and device based on gradient test, computer equipment and a computer readable storage medium, which can effectively improve the detection performance of a forward scattering radar on a moving target and solve the problem of serious detection performance loss in the prior art.
One aspect of the present application provides a forward scattering radar moving target detection method based on a gradient test, including:
step S1: the problem of judging whether the echo signal received by the forward scattering radar contains the target signal is expressed as binary hypothesis test, and the hypothesis that the target exists is expressedThe echo signal received by the radar contains a target signalDirect wave signal and noise, in the assumption that the target is absent +.>And if the echo signal received by the radar contains a direct wave signal and noise, the binary hypothesis test is expressed as follows:
wherein,representing echo signals +.>Representing the target signal +_>Representing direct wave signal, +.>Representing noise->And->Representing the complex amplitudes of the target signal and the direct wave signal, respectively, noise +.>Obeying complex Gaussian distribution, the mean value is 0, and the covariance matrix isWherein->Representing variance->Representing the identity matrix;
step S2: based on assumptions of the presence of the targetStatistical distribution of lower target signal, direct wave signal and noise, assumption that target is absent ∈>Statistical distribution of lower direct wave signal and noise, calculating assumption of target existence +.>Probability density function of lower echo signal and assumption that target is not present +.>A probability density function of the lower echo signal;
step S3: based on the binary hypothesis test, using the hypothesis of the presence of the target calculated in step S2Probability density function of lower echo signal and assumption that target is not present +.>Setting an expression of complex parameter gradient test by a probability density function of the lower echo signal;
step S4: based on assumptions of the presence of the targetProbability density function of lower echo signal and assumption that target is not presentProbability density function of lower echo signal, calculating assumption of target existence +.>Complex amplitude of lower target signal->Maximum likelihood estimate of (2) and the assumption that the target is absent +.>Complex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->Maximum likelihood estimate of (a);
step S5: the assumption of the existence of the object calculated in step S4Complex amplitude of lower target signal->Maximum likelihood estimate of (2) and the assumption that the target is absent +.>Complex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->Substituting the maximum likelihood estimation value of the step (3) into the complex parameter gradient test expression set in the step (3) to obtain the gradient test statistic expression;
step S6: substituting the echo signal to be detected received by the forward scattering radar into an expression of the gradient test statistic to obtain the gradient test statistic, comparing the gradient test statistic with a set threshold, judging that the echo signal contains the target signal if the gradient test statistic is larger than the set threshold, and otherwise, judging that the echo signal does not contain the target signal.
Preferably, in step S2, assumption of existence of the object calculated in 2Probability density function of lower echo signalAnd the assumption that the target does not exist ∈ ->Probability density function of lower echo signal>The method comprises the following steps of:
wherein,representing the 2 norms of the vector, ">Expressed as +.>The bottom index, N, represents the number of echo signal sampling points.
Preferably, in step S3, the expression of the complex parameter gradient test is:
wherein,represents the partial derivative->Expressed as logarithm->，/>，，/>Indicating transpose,/->Represents the conjugate transpose->Representation->Hypothesis of the presence at the target->Maximum likelihood estimate under +.>Representation->Hypothesis of absence of target->Maximum likelihood estimate under +.>Representation ofHypothesis of absence of target->The following values.
Preferably, in step S4, the assumption of the presence of the targetComplex amplitude of lower target signal->The maximum likelihood estimate of (2) is:
wherein,,/>,/>，
hypothesis that target does not existComplex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->The maximum likelihood estimate of (2) is:
according toIs defined as follows:
。
preferably, the expression of the gradient test statistic obtained in step S5 is:
wherein,,/>。
another aspect of the present application provides a forward scatter radar moving object detection apparatus based on a gradient test, including:
binary hypothesis testing represents the module: the problem of judging whether the echo signal received by the forward scattering radar contains the target signal is expressed as binary hypothesis test, and the hypothesis that the target exists is expressedThe echo signal received by the radar contains a target signal, a direct wave signal and noise, and the assumption that the target is not present is +.>And if the echo signal received by the radar contains a direct wave signal and noise, the binary hypothesis test is expressed as follows:
wherein,representing echo signals +.>Representing the target signal +_>Representing direct wave signal, +.>Representing noise->And->Representing the complex amplitudes of the target signal and the direct wave signal, respectively, noise +.>Obeying complex Gaussian distribution, the mean value is 0, and the covariance matrix isWherein->Representing variance->Representing the identity matrix;
probability density function calculation module: based on assumptions of the presence of the targetStatistical distribution of lower target signal, direct wave signal and noise, assumption that target is absent ∈>Statistical distribution of lower direct wave signal and noise, calculating assumption of target existence +.>Probability density function of lower echo signal and assumption that target is not present +.>A probability density function of the lower echo signal;
a test expression setting module: based on the binary hypothesis test, using the hypothesis that the target existsProbability density function of lower echo signal and assumption that target is not present +.>Setting an expression of complex parameter gradient test by a probability density function of the lower echo signal;
maximum likelihood estimate calculation module: based on assumptions of the presence of the targetProbability density function of lower echo signal and assumption that target is not present +.>Probability density function of lower echo signal, calculating assumption of target existence +.>Complex amplitude of lower target signal->Maximum likelihood estimate of (2) and the assumption that the target is absent +.>Complex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->Maximum likelihood estimate of (a);
the statistic expression obtaining module: hypothesis of target PresenceComplex amplitude of lower target signal->Maximum likelihood estimate of (2) and the assumption that the target is absent +.>Complex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->Substituting the maximum likelihood estimation value of the random number into an expression of complex parameter random test to obtain an expression of random test statistics;
and a judging module: substituting the echo signal to be detected received by the forward scattering radar into an expression of the gradient test statistic to obtain the gradient test statistic, comparing the gradient test statistic with a set threshold, judging that the echo signal contains the target signal if the gradient test statistic is larger than the set threshold, and otherwise, judging that the echo signal does not contain the target signal.
A further aspect of the application provides a computer device comprising a memory storing a computer program and a processor implementing the steps of the method described above when the computer program is executed by the processor.
Yet another aspect of the application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method described above.
According to the forward scattering radar moving target detection method and device based on the gradient test, the computer equipment and the computer readable storage medium, which are disclosed by the application, the detection performance of the forward scattering radar on the moving target can be effectively improved.
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For a clearer description of the technical solutions of the present application, the following description will be given with reference to the attached drawings used in the description of the embodiments of the present application, it being obvious that the attached drawings in the following description are only some embodiments of the present application, and that other attached drawings can be obtained by those skilled in the art without the need of inventive effort:
FIG. 1 is a flow chart of a forward scatter radar moving object detection method based on a gradient test according to one embodiment of the present application;
FIG. 2 is a graph showing the variation of detection probability with the direct wave signal to noise spectral density power ratio obtained when the target detection is performed by applying the detection method, the conventional detection method and the ideal detection method when the base line length is 2800 m;
FIG. 3 is a graph showing the variation of the detection probability with the noise spectral density power ratio of the direct wave signal, obtained when the target detection is performed by applying the detection method, the conventional detection method and the ideal detection method, when the base line length is 450 m;
FIG. 4 is a block diagram of a forward scatter radar moving object detection apparatus based on a gradient test according to an embodiment of the present application;
fig. 5 is a block diagram of a computer device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The embodiment of the application provides a forward scattering radar moving target detection method based on a gradient test. FIG. 1 is a flow chart of a forward scatter radar moving object detection method based on a gradient test according to an embodiment of the present application. As shown in fig. 1, the forward scattering radar moving object detection method based on the gradient test according to the embodiment of the present application includes steps S1 to S6.
In step S1, the problem of determining whether the echo signal received by the forward scattering radar receiver contains the target signal is represented as a binary hypothesis test. The radar receiver receives the target signal, noise and direct wave signal when the target is present, and receives the noise and direct wave signal when the target is not present. And sampling the received echo signals to obtain N sampling points.
Assumption of absence of target(hereinafter referred to simply as "hypothesis->") the echo signal received by the forward scatter radar receiver +.>Includes noise->And direct wave signal->Hypothesis of the presence of the target->(hereinafter referred to simply as "hypothesis->") the echo signal received by the forward scatter radar receiver +.>Comprises the target signal->Noise->And direct wave signal->Wherein->Representing a set of N-dimensional complex vectors, the binary hypothesis test is as follows:
(1)
wherein,unknown complex amplitude to be estimated representing the direct wave signal, < +.>Representing the unknown complex amplitude of the target signal to be estimated, noise +.>Is 0 as mean value and 0 as covariance matrix +.>Is a complex Gaussian vector of>Representing variance->Representing the identity matrix.
In step S2, according to the assumption in step S1Distribution of lower target signal, direct wave signal and noise and hypothesis +.>Distribution of lower direct wave signal and noise, calculating echo signal in assumption +.>And assumption->Probability density function below.
Specifically, according to the assumption in step S1Lower direct wave signal->Noise->And target signal->Statistical distribution of (1) and hypothesis->Lower direct wave signal->And noise->Is calculated to get the hypothesis +.>And assumption->Echo signal to be detected under the condition +.>The probability density functions of (a) are:
(2)
(3)
wherein,representing the 2 norms of the vector, ">Expressed as +.>A bottom index.
In step S3, an expression of a complex parameter gradient test (gradient test) is given according to the binary hypothesis test in step S1.
Specifically, according to the binary hypothesis test described in step S1, a complex parameter gradient test expression is given by regarding the complex parameter as a whole.
The expression of the complex parameter gradient test is:
(4)
wherein,represents the partial derivative->Expressed as logarithm->，/>，，/>Indicating transpose,/->Represents the conjugate transpose->Representation->In assumption +.>Maximum likelihood estimate under the condition, +.>Representation->In assumption +.>Maximum likelihood estimate under the condition, +.>Representation->In assumption +.>And (5) taking values under the condition.
In step S4, according to the assumption in step S2Probability density function and hypothesis of lower echo signal +.>Probability density function of lower echo signal, calculating hypothesis +.>Complex amplitude of unknown target signal>Maximum likelihood estimate and hypothesis +.>Of the order of unknownStandard signal complex amplitude +.>Complex amplitude of unknown direct wave signal>And noise variance->Maximum likelihood estimate of (a) in the set.
Specifically, first, according to the assumption described in step S2Probability density function of radar echo signal under condition, calculating assumption +.>Logarithmic pair +.>Is a partial derivative of (c).
According to the assumption set forth in step S2Radar echo signal probability density function under the condition +.>Is calculated as +.>Logarithmic pair->The partial derivatives of (2) are:
(5)
next, the forward scattering radar echo signal in step S2 is assumed to beProbability density function under conditionsTaking the logarithm, and comparing the obtained logarithmic value of probability density function with complex amplitude of unknown target signal +.>Taking the differential to obtain the complex amplitude parameter +.>In assumption +.>The following maximum likelihood estimates are:
(6)
wherein,,/>,/>，/>representing the identity matrix.
Then, on the assumption that the forward scattering radar echo signalThe probability density function->Taking the logarithm, and respectively comparing the obtained logarithmic value of the probability density function with the complex amplitude of the unknown target signal +.>Complex amplitude of unknown direct wave signalAnd variance of noise->Taking the differential to obtain the unknown parameters in the assumption +.>The following maximum likelihood estimation values are respectively:
(7)
(8)
(9)
according toIs defined as follows:
(10)
in step S5, the calculated hypothesis is calculatedAnd assumption->And substituting the maximum likelihood estimated value of the unknown parameter into the expression of the complex parameter gradient test in the step S3 to obtain the expression of gradient test statistic without auxiliary data.
Specifically, the hypothesis calculated in step S4 is calculatedComplex amplitude of unknown target signal under condition +.>Maximum likelihood estimate and hypothesis +.>Complex amplitude of unknown target signal under condition +.>Complex amplitude of unknown direct wave signal +.>And variance of noise->Substituting the maximum likelihood estimation value into the expression of the complex parameter gradient test set in the step S3 and simplifying the expression to obtain the expression of gradient test statistic without auxiliary data, wherein the expression is as follows:
(11)
wherein,,/>。
in step S6, the echo signal to be detected received by the forward scattering radar is substituted into the expression of the gradient test statistic to obtain the gradient test statistic, the gradient test statistic is compared with the set threshold, if the gradient test statistic is greater than the corresponding threshold, the echo signal is determined to contain the target signal, otherwise, the echo signal is determined to not contain the target signal.
Specifically, when the forward scattering radar receives an echo signal, the echo signal received by the forward scattering radar is substituted into the expression of the complex parameter gradient test statistic to obtain the gradient test statisticIn (c) Gradent test statistic->And the set decision threshold->In comparison, if->Greater than the decision thresholdAnd judging that the echo signal contains the target signal, otherwise, judging that the echo signal does not contain the target signal.
The effect of the detection method according to the above embodiment of the present application is further demonstrated by the following simulation experiment.
Experimental Environment and Contents
Experimental environment: MATLAB R2020b, intel (R) Pentium (R) 2 CPU 2.8 GHz,Window 10 flagship edition.
The experimental contents are as follows: setting the carrier frequency to be 5.46GHz, and comparing the performance of the detection method, the ideal detection method and the traditional detection method when the base line length (the distance between a receiver and a transmitter of the forward scattering radar) is 2800m and 450m respectively. Among them, the ideal detection method is only used as a comparison method, and is difficult to obtain in a practical environment.
(II) results of experiments
When the base line length is 2800m and 450m respectively, echo signals are detected by using the detection method based on the gradient test (gradient detection method of the application), the traditional detection method and the ideal detection method according to the embodiment of the application, and the obtained change curves of detection probability along with the noise spectral density power ratio of the direct wave signals are shown in fig. 2 and 3.
As can be seen from fig. 2, the gradient detection method provided by the present application has a performance improvement of about 3dB compared with the conventional detection method when the baseline length is 2800 m. The performance difference is less than 1dB compared to the ideal detection method. The gradient detection method of the application has about 6.5dB performance improvement compared with the traditional detection method when the baseline length is 450 m. The performance difference was 2dB compared to the ideal detection method.
As described above, the simulation experiment verifies the correctness, the effectiveness and the reliability of the gradient detection method provided by the application.
In summary, the detection method according to the above embodiment of the present application aims at the problem of low detection performance of the conventional forward scattering radar moving object detection method, and designs the forward scattering radar moving object detection method based on the gradient test by taking the complex variable as a whole and by means of the gradient test criterion. Monte Carlo simulation experiments show that the method provided by the application is still superior to the traditional method even without any auxiliary data.
The embodiment of the application also provides a forward scattering radar moving target detection device based on the gradient test. Fig. 4 is a block diagram of a forward scatter radar moving object detection apparatus based on a gradient test according to an embodiment of the present application. As shown in fig. 4, the forward scatter radar moving object detection apparatus according to the present embodiment includes:
binary hypothesis testing represents module 101: the problem of judging whether the echo signal received by the forward scattering radar contains the target signal is expressed as binary hypothesis test, and the hypothesis that the target exists is expressedThe echo signal received by the radar contains a target signal, a direct wave signal and noise, and the assumption that the target is not present is +.>And if the echo signal received by the radar contains a direct wave signal and noise, the binary hypothesis test is expressed as follows:
wherein,representing echo signals +.>Representing the target signal +_>Representing direct wave signal, +.>Representing noise->And->Representing the complex amplitudes of the target signal and the direct wave signal, respectively, noise +.>Obeying complex Gaussian distribution, the mean value is 0, and the covariance matrix isWherein->Representing variance->Representing the identity matrix;
probability density function calculation module 102: based on assumptions of the presence of the targetStatistical distribution of lower target signal, direct wave signal and noise, assumption that target is absent ∈>Statistical distribution of lower direct wave signal and noise, calculating assumption of target existence +.>Probability density function and target of lower echo signalNon-existent hypothesis->A probability density function of the lower echo signal;
the test expression setting module 103: based on the binary hypothesis test, using the hypothesis that the target existsProbability density function of lower echo signal and assumption that target is not present +.>Setting an expression of complex parameter gradient test by a probability density function of the lower echo signal;
maximum likelihood estimate calculation module 104: based on assumptions of the presence of the targetProbability density function of lower echo signal and assumption that target is not present +.>Probability density function of lower echo signal, calculating assumption of target existence +.>Complex amplitude of lower target signal->Maximum likelihood estimate of (2) and the assumption that the target is absent +.>Complex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->Maximum likelihood of (2)Estimating a value;
statistics expression acquisition module 105: hypothesis of target PresenceComplex amplitude of lower target signal->Maximum likelihood estimate of (2) and the assumption that the target is absent +.>Complex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->Substituting the maximum likelihood estimation value of the random number into an expression of complex parameter random test to obtain an expression of random test statistics;
the determination module 106: substituting the echo signal to be detected received by the forward scattering radar into an expression of the gradient test statistic to obtain the gradient test statistic, comparing the gradient test statistic with a set threshold, judging that the echo signal contains the target signal if the gradient test statistic is larger than the set threshold, and otherwise, judging that the echo signal does not contain the target signal.
Specific examples of the forward radar moving object detection apparatus based on the gradient test in this embodiment may be referred to above as the limitation of the forward radar moving object detection method based on the gradient test, and will not be described herein. The foregoing modules in the forward radar moving object detection apparatus based on the gradient test may be implemented in whole or in part by software, hardware, or a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
Embodiments of the present application also provide a computer device, which may be a server, and an internal structure thereof may be as shown in fig. 5. The computer device includes a processor, a memory, and a network interface connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used to store operating parameter data for each of the frames. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by a processor, implements the steps of the forward scatter radar moving object detection method according to the present embodiment based on the gradient test.
It will be appreciated by those skilled in the art that the structure shown in FIG. 5 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
The embodiment of the application also provides a computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps of the forward scattering radar moving object detection method based on the gradient test according to the embodiment of the application.
While certain exemplary embodiments of the present application have been described above by way of illustration only, it will be apparent to those of ordinary skill in the art that modifications may be made to the described embodiments in various different ways without departing from the spirit and scope of the application. Accordingly, the drawings and description are to be regarded as illustrative in nature and not as restrictive of the scope of the application, which is defined by the appended claims.
Claims (8)
1. The forward scattering radar moving target detection method based on the gradient test is characterized by comprising the following steps of:
step S1: the problem of judging whether the echo signal received by the forward scattering radar contains the target signal is expressed as binary hypothesis test, and the hypothesis that the target exists is expressedThe echo signal received by the radar contains a target signal, a direct wave signal and noise, and the assumption that the target is not present is +.>And if the echo signal received by the radar contains a direct wave signal and noise, the binary hypothesis test is expressed as follows:
wherein,representing echo signals +.>Representing the target signal +_>Representing direct wave signal, +.>Representing noise->And->Respectively represent target letterComplex amplitude of the signal and the direct wave signal, noise +.>Obeying complex Gaussian distribution with mean value of 0 and covariance matrix of +.>Wherein->Representing variance->Representing the identity matrix;
step S2: based on assumptions of the presence of the targetStatistical distribution of lower target signal, direct wave signal and noise, assumption that target is absent ∈>Statistical distribution of lower direct wave signal and noise, calculating assumption of target existence +.>Probability density function of lower echo signal and assumption that target is not present +.>A probability density function of the lower echo signal;
step S3: based on the binary hypothesis test, using the hypothesis of the presence of the target calculated in step S2Probability density function of lower echo signal and assumption that target is not present +.>Probability density function setting complex for lower echo signalAn expression of the parameter gradient test;
step S4: based on assumptions of the presence of the targetProbability density function of lower echo signal and assumption that target is not present +.>Probability density function of lower echo signal, calculating assumption of target existence +.>Complex amplitude of lower target signal->Maximum likelihood estimate of (2) and the assumption that the target is absent +.>Complex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->Maximum likelihood estimate of (a);
step S5: the assumption of the existence of the object calculated in step S4Complex amplitude of lower target signal->Maximum likelihood estimate of (2) and the assumption that the target is absent +.>Complex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->Substituting the maximum likelihood estimation value of the step (3) into the complex parameter gradient test expression set in the step (3) to obtain the gradient test statistic expression;
step S6: substituting the echo signal to be detected received by the forward scattering radar into an expression of the gradient test statistic to obtain the gradient test statistic, comparing the gradient test statistic with a set threshold, judging that the echo signal contains the target signal if the gradient test statistic is larger than the set threshold, and otherwise, judging that the echo signal does not contain the target signal.
2. The method of claim 1, wherein,
the assumption of the presence of the object calculated in step S2Probability density function of lower echo signal>And the assumption that the target does not exist ∈ ->Probability density function of lower echo signal>The method comprises the following steps of:
wherein,representing the 2 norms of the vector, ">Expressed as +.>The bottom index, N, represents the number of echo signal sampling points.
3. The method of claim 2, wherein,
in step S3, the expression of the complex parameter gradient test is:
wherein,represents the partial derivative->Expressed as logarithm->，/>，，/>Indicating transpose,/->Represents the conjugate transpose->Representation->Hypothesis of the presence at the target->Maximum likelihood estimate under +.>Representation->Hypothesis of absence of target->Maximum likelihood estimate under +.>Representation ofHypothesis of absence of target->The following values.
4. The method of claim 3, wherein,
in step S4, the assumption of the existence of the targetComplex amplitude of lower target signal->The maximum likelihood estimate of (2) is:
wherein,, />, />，
hypothesis that target does not existComplex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->The maximum likelihood estimate of (2) is:
according toIs defined as follows:
。
5. the method of claim 4, wherein,
the expression of the gradient test statistic obtained in step S5 is:
wherein,, />。
6. a forward scatter radar moving object detection apparatus based on a gradient test, comprising:
binary hypothesis testing represents the module: the problem of judging whether the echo signal received by the forward scattering radar contains the target signal is expressed as binary hypothesis test, and the hypothesis that the target exists is expressedThe echo signal received by the radar contains a target signal, a direct wave signal and noise, and the assumption that the target is not present is +.>And if the echo signal received by the radar contains a direct wave signal and noise, the binary hypothesis test is expressed as follows:
wherein,representing echo signals +.>Representing the target signal +_>Representing direct wave signal, +.>Representing noise->And->Representing the complex amplitudes of the target signal and the direct wave signal, respectively, noise +.>Obeying complex Gaussian distribution with mean value of 0 and covariance matrix of +.>Wherein->Representing variance->Representing the identity matrix;
probability density function calculation module: based on assumptions of the presence of the targetStatistical distribution of lower target signal, direct wave signal and noiseAnd the assumption that the target does not exist ∈ ->Statistical distribution of lower direct wave signal and noise, calculating assumption of target existenceProbability density function of lower echo signal and assumption that target is not present +.>A probability density function of the lower echo signal;
a test expression setting module: based on the binary hypothesis test, using the hypothesis that the target existsProbability density function of lower echo signal and assumption that target is not present +.>Setting an expression of complex parameter gradient test by a probability density function of the lower echo signal;
maximum likelihood estimate calculation module: based on assumptions of the presence of the targetProbability density function of lower echo signal and assumption that target is not present +.>Probability density function of lower echo signal, calculating assumption of target existence +.>Complex amplitude of lower target signal->Maximum likelihood estimate of (2) and the assumption that the target is absent +.>Complex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noise->Maximum likelihood estimate of (a);
the statistic expression obtaining module: hypothesis of target PresenceComplex amplitude of lower target signal->Maximum likelihood estimate of (2) and the assumption that the target is absent +.>Complex amplitude of lower target signal->Complex amplitude of direct wave signal +.>And variance of noiseSubstituting the maximum likelihood estimation value of the random number into an expression of complex parameter random test to obtain an expression of random test statistics;
and a judging module: substituting the echo signal to be detected received by the forward scattering radar into an expression of the gradient test statistic to obtain the gradient test statistic, comparing the gradient test statistic with a set threshold, judging that the echo signal contains the target signal if the gradient test statistic is larger than the set threshold, and otherwise, judging that the echo signal does not contain the target signal.
7. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1-5 when the computer program is executed.
8. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1-5.
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