A phased array bad channel automatic detection method, device, storage medium and equipment

Abstract

The specification discloses a phased array channel automatic detection method and device, a storage medium and equipment, which can detect each array element when a large sensor array is running, by performing root mean square value analysis and frequency characteristic analysis on the received signal collected by each array element, to detect each array element, and immediately recalculate the weight coefficient used by the remaining normally working array elements during beam forming when a problem is detected in a certain array element, to ensure that the performance of the entire array is not affected, to improve the quality of the beam pattern, reduce unnecessary sidelobe interference, and improve the accuracy of target azimuth estimation.

Description

Technical Field

[0001] This specification relates to the field of sensor array signal processing technology, and in particular to an automatic detection method, device, storage medium and equipment for phased array bad sectors. Background Technology

[0002] Currently, a key technology in the field of sensor array signal processing, such as radio telescopes, sonar, and radar, is beamforming. It controls the amplitude and phase of each element by adjusting the weight coefficients of each element in a phased array, thereby concentrating energy in a specified direction to improve the efficiency of signal reception or transmission. This results in the array's response being enhanced in the specified direction and weakened in other directions. In this way, the array's output signal has the maximum energy in the desired direction, thus enabling a more accurate estimation of the target's location.

[0003] However, when some array elements are damaged due to aging or other reasons, bad channels can be identified manually from the array elements based on the histogram of the phased array signal. The weighting coefficients of these bad channels can be adjusted to zero to avoid a severe degradation in the quality of the array beammap obtained by the phased array. However, manually identifying bad channels and setting their weighting coefficients to zero is inaccurate. This can lead to interference from responses in other directions affecting the array's response in a specific direction, resulting in a significant increase in sidelobes in the array beammap and poor accuracy in azimuth estimation.

[0004] Therefore, how to improve the accuracy of azimuth estimation when bad channels exist in phased arrays is an urgent problem to be solved. Summary of the Invention

[0005] This specification provides an automatic detection method, apparatus, storage medium, and device for phased array bad sectors, in order to partially solve the aforementioned problems existing in the prior art.

[0006] The following technical solution is adopted in this specification:

[0007] This manual provides an automatic method for detecting bad sectors in a phased array, including:

[0008] Acquire each signal to be detected, wherein each signal to be detected is received by each element of the preset target phased array within a specified time period;

[0009] For each received signal to be detected, the amplitude feature value of the received signal to be detected is determined based on the signal value of the received signal at each time. The received signal to be detected is then detected based on the amplitude feature value and at least one of the preset different detection strategies to obtain the detection result of the array element corresponding to the received signal to be detected. The amplitude feature value is used to reflect the amplitude characteristics of the received signal to be detected within the specified time period, and the detection result is used to characterize whether the array element corresponding to the received signal to be detected is a bad channel.

[0010] Based on the detection results, bad channels in each element of the target phased array are determined, and the weight coefficients corresponding to each element in the target phased array are adjusted according to the bad channels in each element of the target phased array to obtain the adjusted target phased array. The task is then executed through the adjusted target phased array.

[0011] Optionally, for each received signal to be detected, the amplitude characteristic value of the received signal to be detected is determined based on the signal value of the received signal at each time step, specifically including:

[0012] For each received signal to be detected, the root mean square of the signal value at each time step is determined and used as the amplitude characteristic value of the received signal to be detected.

[0013] Optionally, the received signal to be detected is detected according to the amplitude feature value and at least one of the preset different detection strategies to obtain the detection result of the array element corresponding to the received signal to be detected, specifically including:

[0014] According to the preset detection strategy, it is determined whether the amplitude feature value exceeds the preset amplitude feature value threshold;

[0015] If not, a detection result is obtained to characterize the array element corresponding to the received signal to be detected as a bad channel.

[0016] Optionally, the received signal to be detected is detected according to the amplitude feature value and at least one of the preset different detection strategies to obtain the detection result of the array element corresponding to the received signal to be detected, specifically including:

[0017] According to the preset detection strategy, the amplitude feature value is transformed by the distribution characteristics to obtain the transformed amplitude feature value of the received signal to be detected;

[0018] Based on whether the conversion amplitude feature value is within a preset specified data range, the detection result of the array element corresponding to the received signal to be detected is obtained. The specified data range is determined based on the standard deviation of each conversion amplitude feature value of each received signal to be detected.

[0019] Optionally, the received signal to be detected is detected according to the amplitude feature value and at least one of the preset different detection strategies to obtain the detection result of the array element corresponding to the received signal to be detected, specifically including:

[0020] According to the preset detection strategy, for the signal value of the received signal to be detected at each time, the base value corresponding to the signal value of the received signal to be detected at that time is determined based on whether the signal value of the received signal to be detected at that time exceeds the amplitude characteristic value.

[0021] Based on the base value corresponding to the signal value of the received signal to be detected at each time moment, a base value sequence is obtained;

[0022] Determine the difference sequence of the base value sequence, and determine the over-amplitude eigenvalue rate of the received signal to be detected based on the difference sequence;

[0023] The upper and lower limits of the target are determined based on the over-amplitude eigenvalue rate of each received signal to be detected;

[0024] The detection result of the array element corresponding to the received signal to be detected is obtained based on whether the over-amplitude eigenvalue rate of the received signal to be detected is within the target upper and lower limits.

[0025] Optionally, based on the bad channels in each element of the target phased array, the weight coefficients corresponding to each element in the target phased array are adjusted to obtain an adjusted target phased array, specifically including:

[0026] The weight coefficients corresponding to bad channels in each element of the target phased array are adjusted to specified values ​​to obtain the initially adjusted target phased array.

[0027] The target phased array is initially tuned to obtain a target beam pattern. Based on the target beam pattern, the weight coefficients corresponding to each array element in the target phased array are adjusted to obtain the adjusted target phased array.

[0028] Optionally, based on the target beam pattern, the weighting coefficients corresponding to each element in the target phased array are adjusted to obtain an adjusted target phased array, specifically including:

[0029] While keeping the total energy of the target beammap constant, the target loss value is determined based on the total sidelobe energy of the target beammap. With minimizing the target loss value as the optimization objective, the weight coefficients corresponding to each element of the target phased array (excluding the bad channels) are adjusted to obtain the adjusted target phased array. The target loss value is positively correlated with the total sidelobe energy. The total energy of the target beammap is used to characterize the sum of signal energy in all directions of the target beammap, and the total sidelobe energy of the target beammap is used to characterize the sum of signal energy in all other directions of the target beammap except for the main lobe.

[0030] This manual provides an automatic phased array bad sector detection device, including:

[0031] The acquisition module is used to acquire each received signal to be detected, wherein each received signal to be detected is received by each array element in the preset target phased array within a specified time period;

[0032] The detection module is used to determine the amplitude feature value of each received signal to be detected based on the signal value of the received signal at each time step, and to detect the received signal to be detected based on the amplitude feature value and at least one of the preset different detection strategies to obtain the detection result of the array element corresponding to the received signal to be detected. The amplitude feature value is used to reflect the amplitude characteristics of the received signal to be detected within the specified time period, and the detection result is used to characterize whether the array element corresponding to the received signal to be detected is a bad channel.

[0033] The execution module is used to determine the bad channels in each element of the target phased array based on the detection results, and adjust the weight coefficients corresponding to each element in the target phased array based on the bad channels in each element of the target phased array to obtain the adjusted target phased array, and perform task execution through the adjusted target phased array.

[0034] This specification provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described automatic phased array bad sector detection method.

[0035] This specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described automatic phased array bad sector detection method.

[0036] The above-mentioned technical solutions adopted in this specification can achieve the following beneficial effects:

[0037] In the automatic bad sector detection method for phased arrays provided in this specification, each received signal to be detected is first acquired. Each received signal to be detected is received by each element of a preset target phased array within a specified time period. Then, for each received signal to be detected, the amplitude characteristic value of the received signal to be detected is determined based on the signal value of the received signal at each moment. Based on the amplitude characteristic value and at least one of the preset different detection strategies, the received signal to be detected is detected to obtain the detection result of the array element corresponding to the received signal to be detected. The amplitude characteristic value is used to reflect the amplitude characteristics of the received signal to be detected within the specified time period, and the detection result is used to characterize whether the array element corresponding to the received signal to be detected is a bad sector. Based on the detection result, bad sectors in each array element of the target phased array are determined. Based on the bad sectors in each array element of the target phased array, the weight coefficients corresponding to each array element in the target phased array are adjusted to obtain the adjusted target phased array. The task is executed through the adjusted target phased array.

[0038] As can be seen from the above method, when a large sensor array is running, the amplitude characteristic value of the received signal to be detected collected by each array element can be analyzed to detect each array element. When a problem is detected in an array element, the weight coefficients used by the remaining normally operating array elements in beamforming can be recalculated immediately to ensure that the performance of the entire array is not affected, thereby improving the quality of the beam pattern, reducing unnecessary sidelobe interference, and improving the accuracy of target azimuth estimation. Attached Figure Description

[0039] The accompanying drawings, which are included to provide a further understanding of this specification and form part of this specification, illustrate exemplary embodiments and are used to explain this specification, but do not constitute an undue limitation thereof. In the drawings:

[0040] Figure 1 This is a flowchart illustrating an automatic bad sector detection method for phased arrays provided in this specification.

[0041] Figure 2 This is a schematic diagram of the target beam pattern provided in this specification;

[0042] Figure 3 This is a schematic diagram of an automatic phased array bad sector detection device provided in this specification.

[0043] Figure 4 This specification provides a corresponding Figure 1 A schematic diagram of an electronic device. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this specification clearer, the technical solutions of this specification will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of them. Based on the embodiments in this specification, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this specification.

[0045] Currently, in fields such as radio telescopes, sonar, and radar that employ sensor array signal processing, phased arrays can typically adjust the amplitude and phase of each element electronically according to pre-determined weighting coefficients. This concentrates energy in the target direction, reduces sidelobes, and forms a beam pointing in a specific direction. When the beam illuminates the target, the target reflects an echo signal. These echo signals are received by the elements of the phased array. Because the received echo signals arrive from different directions, they will have different propagation path lengths, resulting in a phase difference between different elements. By measuring the phase difference between different elements, the direction of arrival of the echo signal can be calculated, thus determining the phase angle of the target.

[0046] In practical applications, phased array elements may become damaged due to aging or other reasons. Because modern phased array antennas are highly integrated, with elements and related electronic equipment closely arranged, replacing a single element becomes extremely complex. Furthermore, in some cases, elements may be encapsulated within a module, meaning replacing one element might require replacing the entire module. Therefore, when the number of damaged elements in a phased array is small, repairs are not immediately undertaken. To prevent a significant drop in beamform quality due to damaged elements (i.e., bad channels), it is necessary to promptly identify which elements in the phased array are bad channels and adjust the weighting coefficients corresponding to each element to improve the beamforming performance of the phased array and enhance the accuracy of azimuth estimation in the presence of bad channels.

[0047] The technical solutions provided in the various embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0048] Figure 1 This is a flowchart illustrating an automatic phased array bad sector detection method provided in this specification, including the following steps:

[0049] S101: Acquire each receiver signal to be detected, wherein each receiver signal to be detected is received by each element in the preset target phased array within a specified time period.

[0050] In this specification, the service platform can perform bad channel detection on the target phase array at specified time intervals to detect bad channels contained in the target phase array. By setting the weight coefficient of the bad channel to a specified value and adjusting the weight coefficients of other array elements in the target phase array other than the bad channel according to the beam pattern formation, the platform can avoid the situation where the quality of the beam pattern formed by the phased array is greatly reduced due to the presence of bad channels.

[0051] Prior to this, the business platform needs to acquire the received signals to be detected collected by each array element in the target phase array within a specified time period. Then, based on the received signals to be detected collected by each array element in the target phase array, bad channels can be detected from each array element in the target phase array. Here, each received signal to be detected corresponds one-to-one with each array element. That is, for each array element, the received signal collected by that array element is acquired as the received signal to be detected. At this time, the received signal to be detected collected by that array element corresponds to that array element.

[0052] In the above content, the target phase array can be a phase array that the user can configure according to actual needs to perform automatic bad sector detection.

[0053] In this specification, the executing entity used to implement the automatic phased array bad sector detection method can refer to a designated device set up by the business platform, such as a server, Internet of Things (IoT) device, or a terminal device such as a desktop computer or laptop computer. For ease of description, the following description will only use a server as the executing entity to illustrate the automatic phased array bad sector detection method provided in this specification.

[0054] S102: For each received signal to be detected, determine the amplitude characteristic value of the received signal to be detected based on the signal value of the received signal to be detected at each time. Detect the received signal to be detected based on the amplitude characteristic value and at least one of the preset different detection strategies to obtain the detection result of the array element corresponding to the received signal to be detected. The amplitude characteristic value is used to reflect the amplitude characteristics of the received signal to be detected within the specified time period, and the detection result is used to characterize whether the array element corresponding to the received signal to be detected is a bad channel.

[0055] In this specification, after acquiring each received signal to be detected, the server can determine the amplitude characteristic value of the received signal to be detected based on the signal value of the received signal at each time moment. The specific formula is as follows:

[0056]

[0057] In the above formula, m = 0, 1, 2, ..., M-1 are the indices of the array elements in the phased array, M is the total number of array elements in the phased array, and x... m [k] is used to characterize the signal value of the received signal to be detected received by the m-th array element at time k, N is the total number of times included in the specified time period, and Rms[m] is the amplitude characteristic value of the received signal to be detected corresponding to the m-th array element of the phased array.

[0058] As can be seen from the above formula, the server can determine the root mean square of the signal value of each received signal at each time step, and use it as the amplitude characteristic value of the received signal.

[0059] Furthermore, after determining the amplitude characteristic value of each received signal to be detected, the server can detect each received signal to be detected according to at least one of the preset different detection strategies, so as to detect bad channels in each array element contained in the target phased array.

[0060] The aforementioned detection strategies can include three types. The first strategy directly detects bad channels in the array elements corresponding to each received signal based on its amplitude characteristic value. The second strategy detects bad channels in the array elements corresponding to each received signal based on the logarithmic distribution and statistical characteristics of its amplitude characteristic values. The third strategy detects bad channels in the array elements corresponding to each received signal based on the frequency characteristics of its amplitude characteristic values. These three detection strategies will be explained in detail below.

[0061] Specifically, if the detection strategy described above is the first detection strategy, the server can determine whether the amplitude feature value exceeds the preset amplitude feature value threshold according to the preset detection strategy. If yes, a detection result is obtained to indicate that the array element corresponding to the received signal to be detected is not a bad channel; otherwise, a detection result is obtained to indicate that the array element corresponding to the received signal to be detected is a bad channel. The specific details can be found in the following formula:

[0062]

[0063] In the above formula, CHI[m] is the detection result of whether the m-th array element contained in the phased array is a bad channel. 1 indicates that the array element cannot work properly, that is, it is a bad channel, and 0 indicates that the array element is not a bad channel. EPS is the preset amplitude characteristic value threshold, which can be set according to actual needs. For example, EPS can be set to 1e-10, etc.

[0064] If the detection strategy described above is the second detection strategy, the server can perform distribution characteristic transformation on the amplitude feature value according to the preset detection strategy to obtain the transformed amplitude feature value of the received signal to be detected. The specific formula can be found in the following formula:

[0065] Rms_log[m] = log 10 (Rms[m])

[0066] In the above formula, Rms_log[m] is the conversion amplitude characteristic value of the received signal to be detected corresponding to the m-th element of the phased array.

[0067] As can be seen from the above formula, the server can reduce the data skew by converting the amplitude characteristic value of the received signal to be detected into a logarithmic form, making the amplitude characteristic value of each received signal to be detected closer to a normal distribution. This facilitates the detection of bad channels for each array element based on the distribution and statistical characteristics of the amplitude characteristic value of each received signal to be detected.

[0068] Furthermore, the server can obtain the detection result of the array element corresponding to the received signal by determining whether the conversion amplitude characteristic value of the received signal to be detected is within a preset specified data range. The specified data range is determined based on the standard deviation of each conversion amplitude characteristic value of each received signal to be detected, as shown in the following formula:

[0069]

[0070] In the above formula, m is the mean of each conversion amplitude characteristic value of each received signal to be detected, and σ is the standard deviation of each conversion amplitude characteristic value of each received signal to be detected. The specified data range is then determined as follows:

[0071] U b =m+3σ

[0072] U l =m-3σ

[0073]

[0074] In the above formula, U b This refers to the upper limit of the specified data range, U l This is the lower limit of the specified data range. CHI2[m] is the detection result after detecting the received signal corresponding to the m-th array element in the phased array according to the second detection strategy mentioned above. 1 indicates that the array element is a bad channel, and 0 indicates that the array element is not a bad channel.

[0075] If the detection strategy described above is the third detection strategy, the server can determine the basic value corresponding to the signal value of the received signal at each time step based on whether the signal value of the received signal at that time step exceeds the amplitude characteristic value corresponding to the received signal. Therefore, based on the basic values ​​corresponding to the signal value of the received signal at each time step, a basic value sequence corresponding to the received signal can be obtained. For details, please refer to the following formula:

[0076]

[0077] In the above formula, y m [k] represents the base value of the detected received signal corresponding to the m-th array element in the phased array at time k, x m [k] is the signal value of the received signal to be detected corresponding to the m-th array element in the phased array at time k, and Rms[m] is the amplitude characteristic value of the received signal to be detected corresponding to the m-th array element in the phased array.

[0078] Furthermore, after determining the fundamental value sequence corresponding to the detected received signal, the server can determine the difference sequence of the fundamental value sequence corresponding to the received signal to be detected, and determine the over-amplitude eigenvalue rate of the received signal to be detected based on the difference sequence, as shown in the following formula:

[0079] d m [k] = |y[k+1] - y[k]|

[0080]

[0081] In the above formula, d m [k] is the absolute value of the difference sequence of the basic value sequence corresponding to the received signal to be detected, y[k+1] is the value of the (k+1)th element in the basic value sequence corresponding to the received signal to be detected, y[k] is the value of the kth element in the basic value sequence corresponding to the received signal to be detected, RMSCR[m] is the over-amplitude eigenvalue rate of the received signal to be detected corresponding to the mth array element in the phased array, and N is the total number of elements in the difference sequence of the basic value sequence corresponding to the received signal to be detected.

[0082] Furthermore, the server can determine the target upper and lower limits based on the over-amplitude eigenvalue rate of each received signal to be detected.

[0083] Specifically, the server can determine the median of the over-amplitude eigenvalue rate of each received signal to be detected, as a reference median. Then, based on the over-amplitude eigenvalue rate of each received signal to be detected and the reference median, the converted over-amplitude eigenvalue rate of each received signal to be detected can be determined. The specific formula can be found in the following formula:

[0084] RMS n [m] = |RMSCR[m] - med|

[0085] In the above formula, RMS n [m] is the converted amplitude eigenvalue rate of the received signal corresponding to the m-th element in the phased array, and med is the reference median.

[0086] Furthermore, the server can obtain a target over-amplitude eigenvalue rate sequence based on the over-amplitude eigenvalue rate after conversion for each received signal to be detected, and determine the median of each over-amplitude eigenvalue rate contained in the target over-amplitude eigenvalue rate sequence as the target median. Then, based on the target median, the target upper and lower limits can be determined, as shown in the following formula:

[0087] RMSCR Lb =med-4.4478*med_n

[0088] RMSCR Ub =med + 4.4478 * med_n

[0089] In the above formula, RMSCR Ub That is, the upper limit of the target upper and lower limits, RMSCR Lb This is the lower limit of the target's upper and lower limits.

[0090] Furthermore, the server can determine the detection result of the array element corresponding to the received signal based on whether the over-amplitude eigenvalue rate of the received signal to be detected is within the target upper and lower limits. The specific formula is as follows:

[0091]

[0092] In the above formula, CHI3[m] is the detection result after detecting the received signal corresponding to the m-th array element in the phased array according to the third detection strategy mentioned above. 1 indicates that the array element is a bad channel, and 0 indicates that the array element is not a bad channel.

[0093] It should be noted that in practical applications, the three detection strategies mentioned above can be used individually, in combination of two, or all three simultaneously. In order to improve the accuracy of detecting bad channels from the array elements contained in the phased array, the server can simultaneously employ the three detection strategies mentioned above to detect the target phased array.

[0094] Specifically, the server can determine whether each element in the target phased array is a bad channel based on the detection results obtained from each of the detection strategies described above. The specific formula can be found in the following formula:

[0095]

[0096] In the above formula, CHI[m] is the final detection result corresponding to the m-th array element in the target phased array. 1 indicates that the array element is a bad channel, and 0 indicates that the array element is not a bad channel.

[0097] S103: Based on the detection results, determine the bad channels in each element of the target phased array, and adjust the weight coefficients corresponding to each element of the target phased array according to the bad channels in each element of the target phased array to obtain the adjusted target phased array, and perform task execution through the adjusted target phased array.

[0098] In this specification, after determining the detection result of each element in the target phased array, the server can identify bad channels in each element of the target phased array and adjust the weight coefficients corresponding to the bad channels in each element of the target phased array to a specified value to obtain the initially adjusted target phased array. Then, the target beam pattern can be obtained through the initially adjusted target phased array. Based on the target beam pattern, the weight coefficients corresponding to each element in the target phased array can be adjusted to obtain the adjusted target phased array. The specified value here can be set according to actual needs, for example, it can be set to 0.

[0099] Specifically, the server can determine the target loss value based on the total sidelobe energy of the target beammap while keeping the total energy of the target beammap unchanged. With minimizing the target loss value as the optimization objective, the server adjusts the weight coefficients corresponding to each array element in the target phased array except for bad channels to obtain the adjusted target phased array.

[0100] The target loss value is positively correlated with the total sidelobe energy. The total energy of the target beam pattern is used to characterize the sum of signal energy in all directions of the target beam pattern. The total sidelobe energy of the target beam pattern is used to characterize the sum of signal energy in all other directions of the target beam pattern except for the main lobe.

[0101] It should be noted that the target beam pattern contains a main lobe and side lobes. The main lobe refers to the lobe in the target beam pattern with the maximum radiation direction; it represents the maximum response or gain of the antenna or sensor array in a specific direction. The main lobe typically corresponds to the main propagation direction of the signal and is the region with the most concentrated energy. Side lobes refer to other lobes in the target beam pattern besides the main lobe. They contain some energy, but are weaker than the main lobe. The presence of side lobes can interfere with target detection and signal recognition because they may receive signals from non-primary directions, thus affecting the judgment of the primary signal. Therefore, in radar and acoustics, the presence of side lobes can interfere with sound source localization and sound recognition, and thus needs to be suppressed and eliminated. Specifically, as shown below... Figure 2 As shown.

[0102] Figure 2 This is a schematic diagram of the target beam pattern provided in this specification.

[0103] exist Figure 2 In the diagram, curve 1 is the Chebyshev window function beammap when all elements in the target phased array are working normally; curve 2 is the Chebyshev window function beammap when the 20th element in the target phased array is not working properly and its weight coefficient is directly set to zero; and curve 3 is the beammap after the 20th element is not working properly, its weight coefficient is set to zero, and the weight coefficients of other elements are adjusted.

[0104] For ease of understanding, the following uses M as the number of elements in the target phased array, where M = 64, and the coordinates of each element's position are {x}. m Taking m = 0, 1, 2, ..., M-1 as an example, this paper details the method of adjusting the weight coefficients of each array element in the target phased array to obtain the adjusted target phased array.

[0105] Specifically, when the number of elements in the target phased array is M, the beam pattern of the target phased array can be represented as:

[0106]

[0107] In the above formula, A(θ) is the radiation intensity of the array at angle θ, k = 2πf / c is called the wavenumber, and a m These are beamforming weighting coefficients, also known as window functions. The window function here can be, for example, a Chebyshev window, a Hanning window, etc. Here, j represents the imaginary part, and x represents the imaginary part. m Let be the position coordinates of the m-th element in the target phased array.

[0108] Furthermore, when there are F array elements with bad channels at corresponding positions {xf1, xf2, ..., xfF}, the weight coefficients of these F array elements can be adjusted to 0. In this way, the weight coefficients of the other array elements in the target phased array, excluding the bad channels, can be adjusted to obtain the adjusted target phased array.

[0109] Specifically, if the main lobe range is [-B, B] in the above target beam pattern, then the side lobe range is [-90°, -B / 2)∪(B / 2, 90°]. In this case, the total energy of the above target beam pattern can be referred to the following formula:

[0110]

[0111] The total sidelobe energy of the target beam pattern described above can be obtained using the following formula:

[0112]

[0113] Furthermore, the server can adjust the weight coefficients of each array element, excluding bad channels, with the optimization objective of minimizing the total energy of the sidelobes of the target beammap while keeping the total energy of the target beammap obtained through the target phased array constant.

[0114] Furthermore, after obtaining the adjusted target phased array, the server can generate a beammap based on the adjusted weight coefficients corresponding to each array element in the adjusted target phased array, and perform task execution based on the generated beammap.

[0115] The tasks mentioned above can be determined according to actual needs, such as target detection and localization tasks, sonar image generation tasks, etc.

[0116] As can be seen from the above method, the server can perform root mean square value analysis and frequency characteristic analysis on the received signal collected by each array element during the operation of a large sensor array to detect each array element. When a problem is detected in an array element, the server can immediately recalculate the weight coefficients used by the remaining normally operating array elements in beamforming to ensure that the performance of the entire array is not affected, thereby improving the quality of the beam pattern, reducing unnecessary sidelobe interference, and improving the accuracy of target azimuth estimation.

[0117] The above describes one or more methods for automatic detection of bad sectors in phased arrays as described in this specification. Based on the same approach, this specification also provides corresponding automatic detection devices for bad sectors in phased arrays, such as... Figure 3 As shown.

[0118] Figure 3 A schematic diagram of an automatic phased array bad sector detection device provided in this specification includes:

[0119] The acquisition module 301 is used to acquire each detected received signal, wherein each detected received signal is received by each array element in the preset target phased array within a specified time period;

[0120] The detection module 302 is used to determine the amplitude feature value of each received signal to be detected based on the signal value of the received signal at each time moment, and to detect the received signal to be detected based on the amplitude feature value and at least one of the preset different detection strategies to obtain the detection result of the array element corresponding to the received signal to be detected. The amplitude feature value is used to reflect the amplitude characteristics of the received signal to be detected within the specified time period, and the detection result is used to characterize whether the array element corresponding to the received signal to be detected is a bad channel.

[0121] The execution module 303 is used to determine the bad channels in each array element of the target phased array according to the detection result, and adjust the weight coefficients corresponding to each array element in the target phased array according to the bad channels in each array element of the target phased array to obtain the adjusted target phased array, and perform task execution through the adjusted target phased array.

[0122] Optionally, the detection module 302 is specifically used to determine the root mean square of the signal value of each received signal to be detected at each time step, and use it as the amplitude characteristic value of the received signal to be detected.

[0123] Optionally, the detection module 302 is specifically used to determine whether the amplitude feature value exceeds a preset amplitude feature value threshold according to a preset detection strategy; if not, a detection result is obtained to characterize the array element corresponding to the received signal to be detected as a bad channel.

[0124] Optionally, the detection module 302 is specifically used to: perform distribution characteristic transformation on the amplitude feature value according to a preset detection strategy to obtain the transformed amplitude feature value of the received signal to be detected; and obtain the detection result of the array element corresponding to the received signal to be detected according to whether the transformed amplitude feature value is within a preset specified data range, wherein the specified data range is determined based on the standard deviation of each transformed amplitude feature value of each received signal to be detected.

[0125] Optionally, the detection module 302 is specifically configured to: according to a preset detection strategy, for the signal value of the received signal to be detected at each time step, determine the basic value corresponding to the signal value of the received signal to be detected at that time step based on whether the signal value of the received signal to be detected at that time step exceeds the amplitude feature value; obtain a basic value sequence based on the basic value corresponding to the signal value of the received signal to be detected at each time step; determine the difference sequence of the basic value sequence, and determine the over-amplitude feature value rate of the received signal to be detected based on the difference sequence; determine the target upper and lower limits based on the over-amplitude feature value rate of each received signal to be detected; and obtain the detection result of the array element corresponding to the received signal to be detected based on whether the over-amplitude feature value rate of the received signal to be detected is within the target upper and lower limits.

[0126] Optionally, the execution module 303 is specifically used to adjust the weight coefficients corresponding to bad channels in each array element of the target phased array to a specified value to obtain the initially adjusted target phased array; obtain the target beam pattern through the initially adjusted target phased array, and adjust the weight coefficients corresponding to each array element in the target phased array according to the target beam pattern to obtain the adjusted target phased array.

[0127] Optionally, the execution module 303 is specifically configured to, while keeping the total energy of the target beammap unchanged, determine the target loss value based on the total energy of the sidelobes of the target beammap, and adjust the weight coefficients corresponding to each array element of the target phased array except for the bad channels with minimizing the target loss value as the optimization objective, to obtain an adjusted target phased array. The target loss value is positively correlated with the total energy of the sidelobes. The total energy of the target beammap is used to characterize the sum of signal energy in all directions of the target beammap, and the total energy of the sidelobes of the target beammap is used to characterize the sum of signal energy in all other directions of the target beammap except for the main lobe.

[0128] This specification also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 An automatic method for detecting bad sectors in a phased array is provided.

[0129] This instruction manual also provides Figure 4 One of the corresponding Figure 1 A schematic diagram of the structure of an electronic device. (e.g.) Figure 4 At the hardware level, the electronic device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for the business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then runs it to achieve the above-mentioned functions. Figure 1The described automatic bad sector detection method for phased arrays. Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of hardware and software, etc. That is to say, the execution subject of the following processing flow is not limited to individual logic units, but can also be hardware or logic devices.

[0130] Improvements in a technology can be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many improvements to the methodology can now be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that an improvement in methodology cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog are the most commonly used. Those skilled in the art should understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0131] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0132] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0133] For ease of description, the above devices are described in terms of function, divided into various units. Of course, in implementing this specification, the functions of each unit can be implemented in one or more software and / or hardware components.

[0134] Those skilled in the art will understand that embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0135] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0136] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0137] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0138] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0139] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0140] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0141] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0142] Those skilled in the art will understand that the embodiments of this specification can be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0143] This specification can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a specific task or implement a specific abstract data type. This specification can also be practiced in distributed computing environments, where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0144] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0145] The above description is merely an embodiment of this specification and is not intended to limit this specification. Various modifications and variations can be made to this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this specification should be included within the scope of the claims of this specification.

Claims

1. An automatic method for detecting bad sectors in a phased array, characterized in that, include: Acquire each signal to be detected, wherein each signal to be detected is received by each element of the preset target phased array within a specified time period; For each received signal to be detected, the root mean square of the signal value of the received signal at each time step is determined and used as the amplitude characteristic value of the received signal to be detected. The received signal to be detected is detected based on the amplitude feature value and at least one of the preset different detection strategies to obtain the detection result of the array element corresponding to the received signal to be detected. The amplitude feature value reflects the amplitude characteristics of the received signal to be detected within the specified time period, and the detection result characterizes whether the array element corresponding to the received signal to be detected is a bad channel. The detection strategies include: a first detection strategy for directly detecting bad channels in the array element corresponding to each received signal to be detected based on the amplitude feature value of each received signal to be detected; a second detection strategy for detecting bad channels in the array element corresponding to each received signal to be detected based on the logarithmic distribution and statistical characteristics of the amplitude feature values ​​of each received signal to be detected; and a third detection strategy for determining target upper and lower limits based on the over-amplitude feature value rate of each received signal to be detected, and detecting bad channels in the array element corresponding to each received signal to be detected based on whether the over-amplitude feature value rate of each received signal to be detected is within the target upper and lower limits. Based on the detection results, bad channels in each element of the target phased array are determined, and the weight coefficients corresponding to each element in the target phased array are adjusted according to the bad channels in each element of the target phased array to obtain the adjusted target phased array. The task is then executed through the adjusted target phased array.

2. The method as described in claim 1, characterized in that, Based on the amplitude feature value and at least one preset detection strategy, the received signal to be detected is detected to obtain the detection result of the array element corresponding to the received signal to be detected, specifically including: According to the preset detection strategy, it is determined whether the amplitude feature value exceeds the preset amplitude feature value threshold; If not, a detection result is obtained to characterize the array element corresponding to the received signal to be detected as a bad channel.

3. The method as described in claim 1, characterized in that, Based on the amplitude feature value and at least one preset detection strategy, the received signal to be detected is detected to obtain the detection result of the array element corresponding to the received signal to be detected, specifically including: According to the preset detection strategy, the amplitude feature value is transformed by the distribution characteristics to obtain the transformed amplitude feature value of the received signal to be detected; Based on whether the conversion amplitude feature value is within a preset specified data range, the detection result of the array element corresponding to the received signal to be detected is obtained. The specified data range is determined based on the standard deviation of each conversion amplitude feature value of each received signal to be detected.

4. The method as described in claim 1, characterized in that, Based on the amplitude feature value and at least one preset detection strategy, the received signal to be detected is detected to obtain the detection result of the array element corresponding to the received signal to be detected, specifically including: According to the preset detection strategy, for the signal value of the received signal to be detected at each time, the base value corresponding to the signal value of the received signal to be detected at that time is determined based on whether the signal value of the received signal to be detected at that time exceeds the amplitude characteristic value. Based on the base value corresponding to the signal value of the received signal to be detected at each time moment, a base value sequence is obtained; Determine the difference sequence of the base value sequence, and determine the over-amplitude eigenvalue rate of the received signal to be detected based on the difference sequence; The upper and lower limits of the target are determined based on the over-amplitude eigenvalue rate of each received signal to be detected; The detection result of the array element corresponding to the received signal to be detected is obtained based on whether the over-amplitude eigenvalue rate of the received signal to be detected is within the target upper and lower limits.

5. The method as described in claim 1, characterized in that, Based on the bad channels in each element of the target phased array, the weight coefficients corresponding to each element in the target phased array are adjusted to obtain the adjusted target phased array, specifically including: The weight coefficients corresponding to bad channels in each element of the target phased array are adjusted to specified values ​​to obtain the initially adjusted target phased array. The target phased array is initially tuned to obtain a target beam pattern. Based on the target beam pattern, the weight coefficients corresponding to each array element in the target phased array are adjusted to obtain the adjusted target phased array.

6. The method as described in claim 5, characterized in that, Based on the target beam pattern, the weight coefficients corresponding to each element in the target phased array are adjusted to obtain the adjusted target phased array, specifically including: While keeping the total energy of the target beammap constant, the target loss value is determined based on the total sidelobe energy of the target beammap. With minimizing the target loss value as the optimization objective, the weight coefficients corresponding to each element of the target phased array (excluding the bad channels) are adjusted to obtain the adjusted target phased array. The target loss value is positively correlated with the total sidelobe energy. The total energy of the target beammap is used to characterize the sum of signal energy in all directions of the target beammap, and the total sidelobe energy of the target beammap is used to characterize the sum of signal energy in all other directions of the target beammap except for the main lobe.

7. An automatic phased array bad sector detection device, characterized in that, include: The acquisition module is used to acquire each received signal to be detected, wherein each received signal to be detected is received by each array element in the preset target phased array within a specified time period; for each received signal to be detected, the root mean square of the signal value of the received signal at each time moment is determined as the amplitude characteristic value of the received signal to be detected. A detection module is configured to, for each received signal to be detected, determine the amplitude characteristic value of the received signal to be detected based on the signal value of the received signal at each time step, and detect the received signal to be detected based on the amplitude characteristic value and at least one of the preset different detection strategies to obtain the detection result of the array element corresponding to the received signal to be detected. The amplitude characteristic value reflects the amplitude characteristics of the received signal to be detected within the specified time period, and the detection result characterizes whether the array element corresponding to the received signal to be detected is a bad channel. The detection strategies include: a first detection strategy for directly detecting bad channels of the array element corresponding to each received signal to be detected based on the amplitude characteristic value of each received signal to be detected; a second detection strategy for detecting bad channels of the array element corresponding to each received signal to be detected based on the logarithmic distribution and statistical characteristics of the amplitude characteristic values ​​of each received signal to be detected; and a third detection strategy for determining target upper and lower limits based on the over-amplitude characteristic value rate of each received signal to be detected, and detecting bad channels of the array element corresponding to each received signal to be detected based on whether the over-amplitude characteristic value rate of each received signal to be detected is within the target upper and lower limits. The execution module is used to determine the bad channels in each element of the target phased array based on the detection results, and adjust the weight coefficients corresponding to each element in the target phased array based on the bad channels in each element of the target phased array to obtain the adjusted target phased array, and perform task execution through the adjusted target phased array.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the method described in any one of claims 1 to 6.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method described in any one of claims 1 to 6.

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