阅读说明：本技术 一种基于不确定先验知识的杂波秩估计方法及装置 (Clutter rank estimation method and device based on uncertain priori knowledge ) 是由 阳召成 汪小叶 何凯旋 黄建军 于 2019-10-11 设计创作，主要内容包括：根据本发明实施例公开的一种基于不确定先验知识的杂波秩估计方法及装置,首先根据不确定先验知识确定等效采样阵列的阵元位置,并根据信号的空域频率计算对应的信号带宽；然后计算对应于阵元位置的等效采样阵列的阵列孔径；最后基于信号带宽以及等效采样阵列的阵列孔径,对阵列雷达预设杂波片方向角的杂波秩进行估计。通过本发明的实施,可以有效提高杂波秩估计的鲁棒性,从而保障了滤波器的杂波抑制性能,并且在正侧视及非正侧视机载雷达上均能良好应用。(According to the clutter rank estimation method and device based on uncertain priori knowledge disclosed by the embodiment of the invention, firstly, the array element position of an equivalent sampling array is determined according to the uncertain priori knowledge, and the corresponding signal bandwidth is calculated according to the spatial frequency of a signal; then calculating the array aperture of the equivalent sampling array corresponding to the array element position; and finally, estimating the clutter rank of the preset clutter chip direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array. By implementing the method, the robustness of clutter rank estimation can be effectively improved, so that the clutter suppression performance of the filter is guaranteed, and the method can be well applied to both front-view and non-front-view airborne radars.)

1. A clutter rank estimation method based on uncertain priori knowledge is characterized by comprising the following steps:

determining the array element position of the equivalent sampling array according to uncertain prior knowledge;

calculating corresponding signal bandwidth according to the spatial domain frequency of the signal;

calculating the array aperture of the equivalent sampling array corresponding to the array element position;

and estimating the clutter rank of the preset clutter slice direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array.

2. The method of clutter rank estimation of claim 1, wherein the determining array element positions of an equivalent sampling array based on uncertain prior knowledge comprises:

acquiring a space-time steering vector component model corresponding to the nth array unit and the mth pulse echo of the array radar; the model of the space-time steering vector component is expressed as:

wherein the ratio of For the ith Doppler frequency, f, of the signal from the q azimuth angle determined using uncertain prior knowledge_s ^(q)Is the spatial frequency of the signal from the q-th azimuth angle, and

and f_s ^(q)Expressed as:

and, d₀，λ₀，T_rAnd theta and phi respectively represent half-wavelength spacing, signal wavelength, minimum pulse repetition frequency, pitch angle, azimuth angle, and v_p'and psi' denote measured airborne platform velocity and yaw angle, respectively, delta psi_mAnd Δ v_pmUncertainty priors, M, representing airborne platform velocity and yaw angle, respectively_eIs the total number of Doppler frequencies, d, of the signal from the q-th azimuth angle_(n-1)Is the relative position of the nth array element of the equivalent sampling array relative to the first array element and has the unit of d₀，t_(m-1)Is the time of transmission of the mth pulse relative to the first pulse, in T_r；

Based on the space-time steering vector component model

3. the method of cluttered rank estimation of claim 2, wherein the computing the corresponding signal bandwidth from the spatial frequency of the signal comprises:

substituting the spatial domain frequency of the signal into a preset signal bandwidth calculation formula to calculate the signal bandwidth of the signal from the q-th azimuth angle; the signal bandwidth calculation formula is expressed as:

4. the method of clutter rank estimation of claim 2, wherein when the equivalent sampling array is a uniform linear array, the computing the array aperture of the equivalent sampling array corresponding to the array element position comprises:

calculating the array aperture of the equivalent sampling array corresponding to the array element position according to a preset first equivalent aperture calculation formula; the first equivalent aperture calculation formula is expressed as:

wherein the content of the first and second substances,

the estimation of the clutter rank of the preset clutter slice direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array comprises the following steps:

substituting the signal bandwidth and the array aperture of the equivalent sampling array into a preset first clutter rank estimation formula to estimate the clutter rank of a preset clutter slice direction angle of the array radar; the first clutter rank estimation formula is expressed as:

wherein the content of the first and second substances,

5. The method of clutter rank estimation of claim 2, wherein when the equivalent sampling array is a sparse array, said computing the array aperture of the equivalent sampling array corresponding to the array element position comprises:

calculating the array aperture of the equivalent sampling array corresponding to the array element position according to a preset second equivalent aperture calculation formula; the second equivalent aperture calculation formula is expressed as:

wherein K is the total number of continuous sub-arrays divided by the sparse array;

the estimation of the clutter rank of the preset clutter slice direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array comprises the following steps:

substituting the signal bandwidth and the array aperture of the equivalent sampling array into a preset second clutter rank estimation formula to estimate the clutter rank of a preset clutter slice direction angle of the array radar; the second clutter rank estimation formula is expressed as:

wherein the content of the first and second substances,

6. A clutter rank estimation apparatus based on uncertain prior knowledge, comprising:

the position determining module is used for determining the array element position of the equivalent sampling array according to the uncertain priori knowledge;

the bandwidth calculation module is used for calculating the corresponding signal bandwidth according to the spatial domain frequency of the signal;

the aperture calculation module is used for calculating the array aperture of the equivalent sampling array corresponding to the array element position;

and the clutter rank estimation module is used for estimating the clutter rank of the preset clutter slice direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array.

7. The cluttered rank estimation apparatus of claim 6, wherein the position determination module is specifically configured to:

acquiring a space-time steering vector component model corresponding to the nth array unit and the mth pulse echo of the array radar; the model of the space-time steering vector component is expressed as:

wherein the ratio of

and f_s ^(q)Expressed as:

and, d₀，λ₀，T_rAnd theta and phi respectively represent half-wavelength spacing, signal wavelength, minimum pulse repetition frequency, pitch angle, azimuth angle, and v_p'and psi' denote measured airborne platform velocity and yaw angle, respectively, delta psi_mAnd Δ v_pmUncertainty priors, M, representing airborne platform velocity and yaw angle, respectively_eIs the total number of Doppler frequencies, d, of the signal from the q-th azimuth angle_(n-1)Is the relative position of the nth array element of the equivalent sampling array relative to the first array element and has the unit of d₀，t_(m-1)Is the time of transmission of the mth pulse relative to the first pulse, in T_r；

Based on the space-time steering vector component model

8. the cluttered rank estimation device of claim 7, wherein the bandwidth calculation module is specifically configured to:

substituting the spatial domain frequency of the signal into a preset signal bandwidth calculation formula to calculate the signal bandwidth of the signal from the q-th azimuth angle; the signal bandwidth calculation formula is expressed as:

9. the apparatus according to claim 7, wherein the aperture calculation module is specifically configured to, when the equivalent sampling array is a uniform linear array:

calculating the array aperture of the equivalent sampling array corresponding to the array element position according to a preset first equivalent aperture calculation formula; the first equivalent aperture calculation formula is expressed as:

wherein the content of the first and second substances,

The clutter rank estimation module is specifically configured to:

substituting the signal bandwidth and the array aperture of the equivalent sampling array into a preset first clutter rank estimation formula to estimate the clutter rank of a preset clutter slice direction angle of the array radar; the first clutter rank estimation formula is expressed as:

wherein the content of the first and second substances,is the signal bandwidth of the signal from the Q-th azimuth, Q is the total number of azimuths,

10. The apparatus according to claim 7, wherein the aperture calculation module is specifically configured to, when the equivalent sampling array is a uniform linear array:

calculating the array aperture of the equivalent sampling array corresponding to the array element position according to a preset second equivalent aperture calculation formula; the second equivalent aperture calculation formula is expressed as:

wherein K is the total number of continuous sub-arrays divided by the sparse array;

the clutter rank estimation module is specifically configured to:

substituting the signal bandwidth and the array aperture of the equivalent sampling array into a preset second clutter rank estimation formula to estimate the clutter rank of a preset clutter slice direction angle of the array radar; the second clutter rank estimation formula is expressed as:

wherein the content of the first and second substances,

Technical Field

The invention relates to the technical field of radar signal processing, in particular to a clutter rank estimation method and device based on uncertain priori knowledge.

Background

Clutter suppression is an important task of effective target detection of an airborne radar, clutter rank is a key parameter required for effective clutter suppression based on clutter subspace or a filter based on feature analysis, and clutter rank estimation is one of core problems concerned by the airborne radar because clutter rank directly influences performance of designed filter clutter suppression.

Disclosure of Invention

The embodiments of the present invention mainly aim to provide a clutter rank estimation method and apparatus based on uncertain priori knowledge, which can at least solve the problems in the related art that when a clutter rank is estimated based on the priori knowledge with errors, the estimated clutter rank has a large error, and the clutter suppression performance of a filter is poor.

In order to achieve the above object, a first aspect of the embodiments of the present invention provides a clutter rank estimation method based on uncertain priori knowledge, including:

determining the array element position of the equivalent sampling array according to uncertain prior knowledge;

calculating corresponding signal bandwidth according to the spatial domain frequency of the signal;

calculating the array aperture of the equivalent sampling array corresponding to the array element position;

and estimating the clutter rank of the preset clutter slice direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array.

In order to achieve the above object, a second aspect of the embodiments of the present invention provides a clutter rank estimation apparatus based on uncertain prior knowledge, the apparatus including:

the position determining module is used for determining the array element position of the equivalent sampling array according to the uncertain priori knowledge;

the bandwidth calculation module is used for calculating the corresponding signal bandwidth according to the spatial domain frequency of the signal;

the aperture calculation module is used for calculating the array aperture of the equivalent sampling array corresponding to the array element position;

and the clutter rank estimation module is used for estimating the clutter rank of the preset clutter slice direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array.

According to the clutter rank estimation method and device based on uncertain priori knowledge disclosed by the embodiment of the invention, firstly, the array element position of an equivalent sampling array is determined according to the uncertain priori knowledge, the corresponding signal bandwidth is calculated according to the spatial frequency of a signal, and then the array aperture of the equivalent sampling array corresponding to the array element position is calculated; and finally, estimating the clutter rank of the preset clutter chip direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array. By implementing the method, the robustness of clutter rank estimation can be effectively improved, so that the clutter suppression performance of the filter is guaranteed, and the method can be well applied to both front-view and non-front-view airborne radars.

Other features and corresponding effects of the present invention are set forth in the following portions of the specification, and it should be understood that at least some of the effects are apparent from the description of the present invention.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a basic flowchart of a method for estimating a clutter rank according to a first embodiment of the present invention;

FIG. 2-1 is a schematic diagram of the clutter rank estimation result of the ULA radar in an ideal environment according to the second embodiment of the present invention;

fig. 2-2 is a schematic diagram of a clutter rank estimation result of a CPA radar in an ideal environment according to a second embodiment of the present invention;

fig. 2-3 are schematic diagrams illustrating clutter rank estimation results of the ULA radar with a priori knowledge error according to the second embodiment of the present invention;

fig. 2-4 are schematic diagrams illustrating clutter rank estimation results of CPA radar with a priori knowledge error according to a second embodiment of the present invention;

fig. 3 is a schematic structural diagram of a clutter rank estimation apparatus according to a third embodiment of the present invention;

fig. 4 is a schematic structural diagram of an electronic device according to a fourth embodiment of the invention.

Detailed Description

In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The first embodiment:

in order to solve the technical problems in the related art that when a clutter rank is estimated based on priori knowledge with errors, the estimated clutter rank has a large error and the clutter suppression performance of a filter is poor, the embodiment provides a clutter rank estimation method based on uncertain priori knowledge, and as shown in fig. 1, the method is a basic flow diagram of the clutter rank estimation method provided by the embodiment, and the clutter rank estimation method provided by the embodiment specifically includes the following steps:

step 101, determining the array element position of the equivalent sampling array according to uncertain prior knowledge.

In an optional implementation manner of this embodiment, a specific implementation manner of step 101 may be represented as follows:

acquiring a space-time steering vector component model corresponding to the nth array unit and the mth pulse echo of the array radar; the model of the space-time steering vector component is expressed as:

wherein the ratio of

For the ith Doppler frequency, f, of the signal from the q azimuth angle determined using uncertain prior knowledge_s ^(q)Is the spatial frequency of the signal from the q-th azimuth angle, andexpressed as:

and f_s ^(q)Expressed as:

and, d₀，λ₀，T_rAnd theta, phi respectively represent half-wavelength spacing, signal wavelength, minimum pulse repetition frequency, pitch angle, azimuth angle, v'_pAnd psi' representing measured airborne platform velocity and yaw angle, respectively, delta psi_mAnd Δ v_pmUncertainty priors, M, representing airborne platform velocity and yaw angle, respectively_eIs the total number of Doppler frequencies, d, of the signal from the q-th azimuth angle_(n-1)Is the relative position of the nth array element of the equivalent sampling array relative to the first array element and has the unit of d₀，t_(m-1)Is the time of transmission of the mth pulse relative to the first pulse, in T_r；

Then based on space-time guide vector component model

Determining array element positions of all equivalent sampling arrays; the array element position is related to the equivalent sampling array and is expressed as:

and 102, calculating the corresponding signal bandwidth according to the spatial domain frequency of the signal.

In an optional implementation manner of this embodiment, in the derivation process of the clutter rank

Signal bandwidth representing the q-th spatial frequency signal, represented by f_s ^(q)The decision, and thus the signal bandwidth calculation formula, can be expressed as:

and further can pass through the space domain frequency signal setSolving to obtain corresponding signal bandwidth set

Wherein Q is the total number of sequences.

And 103, calculating the array aperture of the equivalent sampling array corresponding to the array element position.

In an optional implementation manner of this embodiment, when a Uniform Linear Array (ULA) and a fixed pulse interval structure that satisfy the Nyquist sampling condition are used, the array aperture of the equivalent sampling array corresponding to each array element position is calculated according to a preset first equivalent aperture calculation formula; the first equivalent aperture calculation formula is expressed as:

whereinIs array element position of

The array aperture of the ith equivalent sampling array of (1).

In another alternative embodiment of this embodiment, when the equivalent sampling array is a sparse array, the nyquist sampling condition is satisfied by dividing the sparse array into a plurality of continuous sub-arrays, and in this case, the second equivalent aperture calculation formula for calculating the array aperture of the equivalent sampling array corresponding to each array element position is expressed as:

where K is the total number of consecutive sub-arrays divided by the sparse array.

And step 104, estimating clutter rank of a preset clutter slice direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array.

In the embodiment, correspondingly, on one hand, the signal bandwidth and the aperture of the uniform linear array are substituted into a preset first clutter rank estimation formula to estimate the clutter rank of the array radar at a preset clutter slice direction angle; the first clutter rank estimation formula is expressed as:

wherein the content of the first and second substances,

is the signal bandwidth of the signal from the Q-th azimuth, Q is the total number of azimuths,

for M from the q-th azimuth signal calculated using uncertain prior knowledge_eThe set of array apertures, max (-) for each equivalent sampling array is a function of the maximum.

On the other hand, substituting the signal bandwidth and the aperture of the sparse array into a preset second clutter rank estimation formula to estimate the clutter rank of the array radar at a preset clutter slice direction angle; the second clutter rank estimation formula is expressed as:

wherein the content of the first and second substances,

is the signal bandwidth of the signal from the Q-th azimuth, Q is the total number of azimuths,

is the array aperture of the kth sub-array of the equivalent sampling array of the maximum array aperture of the signal from the qth azimuth angle, and

an array aperture set consisting of array apertures from an array of equivalent samples of the signal at the q-th azimuth.

According to the clutter rank estimation method based on uncertain priori knowledge disclosed by the embodiment of the invention, firstly, the array element position of an equivalent sampling array is determined according to the uncertain priori knowledge, the corresponding signal bandwidth is calculated according to the spatial frequency of a signal, and then the array aperture of the equivalent sampling array corresponding to the array element position is calculated; and finally, estimating the clutter rank of the preset clutter chip direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array. By implementing the method, the robustness of clutter rank estimation can be effectively improved, so that the clutter suppression performance of the filter is guaranteed, and the method can be well applied to both front-view and non-front-view airborne radars.

Second embodiment:

in order to better explain the content of the present invention, the present embodiment explains the effects of the present invention with a specific example.

In the present embodiment, the beneficial effect of the present invention in terms of clutter rank estimation is illustrated by simulation data. Assuming a radar parameter h_p＝125m/s,v_p＝4000m,T _r1/4000s and d₀0.0625m, wherein h_pFor airborne platform height, v_pFor airborne velocity, T_rFor pulse repetition interval, d₀Is an array unit interval. The clutter within a given range is divided into 361 clutter tiles and assuming each clutter tile obeys the same distribution, at a given noise to noise ratio CNR (in decibels), each clutter obeys a mean of 0 and a variance of 10^10/(361CNR)And (4) a complex Gaussian process. Thermal noise compliance of a receiverMean 0, variance

And (4) a complex Gaussian process. In the simulation experiments of this example, all results were calculated as the average of 500 monte carlo experimental results unless otherwise noted.

The accuracy of the clutter rank estimation method of the embodiment in various scenes is verified by using a specific simulation experiment. Assuming a noise-to-noise ratio of 40dB in the experimental scenario, two uniform linear array radars (ULA) with uniformly repeated pulses and two uniform pulse repetition co-prime array radars (CPA) were considered for each of the 4 cases ψ 0 °, β 0.6,1 and ψ 90 °, β 0.6, 1. For the ULA radar, the number of array elements N is 10, and the number of pulses M in a Coherent Processing Interval (CPI) is 10; for CPA radar, the number of array elements is also 10, and the co-prime factor N₁3 and N₂The number of pulses in a CPI is also M10, 5.

In contrast, fig. 2-1 to fig. 2-4 show clutter rank estimation results under different methods according to the present embodiment, where the clutter rank estimation result of the method of the present invention is marked by a solid line, the clutter rank estimation result of the BT method is marked by "o", and the clutter rank estimation result of the C-EBT method is marked by "x", it should be noted that fig. 2-1 shows a schematic diagram of the clutter rank estimation result of the ULA radar under an ideal environment, fig. 2-2 shows a schematic diagram of the clutter rank estimation result of the CPA radar under an ideal environment, fig. 2-3 shows a schematic diagram of the clutter rank estimation result of the ULA radar with a priori knowledge error, and fig. 2-4 shows a schematic diagram of the clutter rank estimation result of the CPA radar with a priori knowledge error.

According to the analysis of the clutter rank estimation result, the clutter rank estimation method provided by the invention can be applied to the front side view radar and the non-front side view radar with psi being more than or equal to 0 DEG and less than or equal to 90 DEG, and the BT theorem and the C-EBT method can only be applied to the front side view condition with psi being 0 deg. It can be seen that in the ideal case (i.e. without a priori knowledge error, av)_pm0 and Δ ψ _m0 °), the result of the method proposed by the invention and the sum of the results of the BT theorem for ULA radars, as appropriate for the positive side with ψ 0 °The results of the C-EBT method for CPA radar are the same. Also, through extensive simulation of various a priori knowledge errors (not shown), it can also be found when a priori knowledge is in error (assuming Δ ν)_pm＝5m/s,Δv′_pm＝0.5Δv_pm,Δψ_m4 ° and Δ ψ'_m＝0.5Δψ_m) The BT theorem and the C-EBT method cannot accurately estimate the clutter rank in a positive sideview radar scene where ψ is 0 °. The proposed method gives better clutter rank estimation at the positive side of 0 ° ° depending on the case, because a priori knowledge of platform speed and yaw angle errors is taken into account in the proposed method. Furthermore, for non-positive side viewing conditions (i.e., 0 ≦ ψ ≦ 90), neither the BT theorem nor the C-EBT method is applicable because the yaw angle is non-zero. However, as can be seen from fig. 2-1 to 2-4, the method proposed by the present invention is still applicable on the non-positive side and can provide satisfactory spur rank estimation. These results show that the method provided by the invention can not only provide good results for the front-side view radar and the non-front-side view radar, but also provide good results under the condition of the error of prior knowledge, thereby being more effective compared with the BT theorem and the C-EBT method.

The third embodiment:

in order to solve the technical problems in the related art that when a clutter rank is estimated based on a priori knowledge with errors, the estimated clutter rank has a large error, and the clutter suppression performance of a filter is poor, the embodiment shows a clutter rank estimation device based on uncertain priori knowledge, and with specific reference to fig. 3, the clutter rank estimation device of the embodiment includes:

the position determining module 301 is configured to determine an array element position of the equivalent sampling array according to the uncertain priori knowledge;

a bandwidth calculating module 302, configured to calculate a corresponding signal bandwidth according to a spatial frequency of a signal;

an aperture calculation module 303, configured to calculate an array aperture of the equivalent sampling array corresponding to the array element position;

and the clutter rank estimation module 304 is configured to estimate a clutter rank of a preset clutter slice direction angle of the array radar based on the signal bandwidth and the array aperture of the equivalent sampling array.

Further, in some embodiments of this embodiment, the position determining module 301 is specifically configured to: firstly, acquiring a space-time steering vector component model corresponding to an nth array unit and an mth pulse echo of an array radar; the model of the space-time steering vector component is expressed as:

wherein the ratio of

For the ith Doppler frequency, f, of the signal from the q azimuth angle determined using uncertain prior knowledge_s ^(q)Is the spatial frequency of the signal from the q-th azimuth angle, and

expressed as:

and f_s ^(q)Expressed as:

and, d₀，λ₀，T_rAnd theta and phi respectively represent half-wavelength intervals,Signal wavelength, minimum pulse repetition frequency, pitch angle, azimuth angle, v'_pAnd psi' representing measured airborne platform velocity and yaw angle, respectively, delta psi_mAnd Δ v_pmUncertainty priors, M, representing airborne platform velocity and yaw angle, respectively_eIs the total number of Doppler frequencies, d, of the signal from the q-th azimuth angle_(n-1)Is the relative position of the nth array element of the equivalent sampling array relative to the first array element and has the unit of d₀，t_(m-1)Is the time of transmission of the mth pulse relative to the first pulse, in T_r；

Then based on space-time guide vector component model

Determining the array element position of the equivalent sampling array; the array element positions are expressed as:

further, in some embodiments of the present embodiment, the bandwidth calculating module 302 is specifically configured to: substituting the spatial domain frequency of the signal into a preset signal bandwidth calculation formula to calculate the signal bandwidth of the signal from the q-th azimuth angle; the signal bandwidth calculation formula is expressed as:

further, in some embodiments of the present embodiment, when the equivalent sampling array is a uniform linear array, the aperture calculating module 303 is specifically configured to: calculating the array aperture of the equivalent sampling array corresponding to the array element position according to a preset first equivalent aperture calculation formula; the first equivalent aperture calculation formula is expressed as:

wherein

Is array element position of The array aperture of the ith equivalent sampling array of (1).

Correspondingly, the clutter rank estimation module 304 is specifically configured to:

substituting the signal bandwidth and the array aperture of the equivalent array into a preset first clutter rank estimation formula, and estimating the clutter rank of a preset clutter slice direction angle of the array radar; the first clutter rank estimation formula is expressed as:

wherein the content of the first and second substances,

is the signal bandwidth of the signal from the Q-th azimuth, Q is the total number of azimuths,

for M from the q-th azimuth signal calculated using uncertain prior knowledge_eThe set of array apertures, max (-) of an equivalent sampling array is a function of the maximum.

In addition, in some embodiments of this embodiment, when the equivalent sampling array is a uniform linear array, the aperture calculation module is specifically configured to: calculating the array aperture of the equivalent sampling array corresponding to the array element position according to a preset second equivalent aperture calculation formula; the second equivalent aperture calculation formula is expressed as:

k is the total number of continuous sub-arrays divided by the sparse array;

correspondingly, the clutter rank estimation module 304 is specifically configured to:

substituting the signal bandwidth and the array aperture of the equivalent sampling array into a preset second clutter rank estimation formula, and estimating the clutter rank of a preset clutter slice direction angle of the array radar; the second clutter rank estimation formula is expressed as:

wherein the content of the first and second substances,

is the signal bandwidth of the signal from the Q-th azimuth, Q is the total number of azimuths,

is the array aperture of the kth sub-array of the equivalent sampling array of the maximum array aperture of the signal from the qth azimuth angle, and

the set of array apertures that is the array aperture of the equivalent sampled array from the q-th azimuth signal is the signal bandwidth.

It should be noted that, the clutter rank estimation method based on uncertain priori knowledge in the foregoing embodiment can be implemented based on the clutter rank estimation device based on uncertain priori knowledge provided in this embodiment, and it can be clearly understood by a person having ordinary skill in the art that, for convenience and simplicity of description, a specific working process of the clutter rank estimation device described in this embodiment may refer to a corresponding process in the foregoing method embodiment, and details are not described here.

By adopting the clutter rank estimation device based on uncertain priori knowledge provided by the embodiment, array element positions of each equivalent sampling array and space domain frequencies corresponding to each equivalent sampling array are respectively determined; calculating the signal bandwidth of each space domain frequency signal according to each space domain frequency; then calculating the aperture of the equivalent sampling array at each array element position; and finally, estimating the clutter rank of the preset clutter chip direction angle of the array radar based on the signal bandwidth and the aperture of the equivalent sampling array. By implementing the method, the robustness of clutter rank estimation can be effectively improved, so that the clutter suppression performance of the filter is guaranteed, and the method can be well applied to both front-view and non-front-view airborne radars.

The fourth embodiment:

the present embodiment provides an electronic device, as shown in fig. 4, which includes a processor 401, a memory 402, and a communication bus 403, wherein: the communication bus 403 is used for realizing connection communication between the processor 401 and the memory 402; the processor 401 is configured to execute one or more computer programs stored in the memory 402 to implement at least one step of the clutter rank estimation method based on uncertain prior knowledge in the first embodiment.

The present embodiments also provide a computer-readable storage medium including volatile or non-volatile, removable or non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, computer program modules or other data. Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash Memory or other Memory technology, CD-ROM (Compact disk Read-Only Memory), Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer.

The computer-readable storage medium in this embodiment may be used for storing one or more computer programs, and the stored one or more computer programs may be executed by a processor to implement at least one step of the method in the first embodiment.

The present embodiment also provides a computer program, which can be distributed on a computer readable medium and executed by a computing device to implement at least one step of the method in the first embodiment; and in some cases at least one of the steps shown or described may be performed in an order different than that described in the embodiments above.

The present embodiments also provide a computer program product comprising a computer readable means on which a computer program as shown above is stored. The computer readable means in this embodiment may include a computer readable storage medium as shown above.

It will be apparent to those skilled in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software (which may be implemented in computer program code executable by a computing device), firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit.

In addition, communication media typically embodies computer readable instructions, data structures, computer program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to one of ordinary skill in the art. Thus, the present invention is not limited to any specific combination of hardware and software.

The foregoing is a more detailed description of embodiments of the present invention, and the present invention is not to be considered limited to such descriptions. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.