An azimuthal history trajectory enhancement method, system, electronic device and storage medium

Abstract

The application provides an azimuth history trajectory enhancement method, system, electronic equipment and storage medium, and belongs to the technical field of sonar signal and information processing. The method comprises the following steps: acquiring several groups of array element channel receiving data in a hydrophone array in multiple preset time intervals; performing beam forming based on the several groups of array element channel receiving data to obtain a time-azimuth history graph, and performing block binarization on the time-azimuth trajectory graph to obtain multiple binary azimuth trajectory graphs; calculating the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, screening the effective connected domains in the binary azimuth trajectory graphs based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, and fusing and splicing to obtain a multi-target trajectory enhanced azimuth history graph. The application performs background noise reduction and trajectory enhancement processing on the passive sonar hydrophone multi-target time-azimuth history image, effectively enhances the contrast between the target and the background, and makes the extracted multi-target trajectory clearer.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of sonar signal and information processing, and particularly relates to a bearing history trajectory enhancement method and system, an electronic device and a storage medium. BACKGROUND

[0002] In the underwater listening scene, sonar is generally used to detect targets. Sonar is divided into active sonar and passive sonar. Active sonar is a hydroacoustic device that detects underwater objects by actively sending sound wave signals. Passive sonar does not send sound wave signals, but detects underwater objects by listening to the sound wave signals emitted by other objects. Passive sonar is usually used in situations where the target needs to be hidden. Passive reception of the radiated noise of the target and the signals emitted by the hydroacoustic device is used to determine the bearing of the target.

[0003] In passive sonar signal processing, the time bearing history graph is a commonly used sonar signal recording and display method. With the advancement of noise reduction technology, the noise of the detected target gradually decreases, which reduces the signal-to-noise ratio of the time bearing history graph, thereby bringing great challenges to target trajectory extraction. Passive sonar usually uses beamforming processing to improve the signal-to-noise ratio and obtain the time bearing history graph of the target. The target trajectory is detected and visualized. If there is a target in the current bearing angle direction, a peak value will appear in the bearing after beamforming. Otherwise, the energy of the bearing is weak and comparable to the background. If the target persists, a relatively stable trajectory will appear on the time bearing history graph of the underwater target. The trajectory changes with the change of the target bearing.

[0004] In practical applications, conventional beamforming has good robustness, but due to its poor angle resolution, high sidelobe, and weak interference suppression capability. Due to the characteristics of the underwater acoustic channel, such as space-time non-stationarity, multi-path, and complex reverberation signals, under the condition of a certain array shape and array aperture, conventional beamforming has difficulty in distinguishing and discovering targets under low signal-to-noise ratio. Due to the non-stationarity of ocean environmental noise in time and the non-uniformity of ocean environmental noise in space, strong interference will appear in the form of patches on the bearing history image. Under the condition of low signal-to-noise ratio, due to the serious background fluctuation, the conventional background equalization has obvious shortcomings, and a large number of snowflake points (i.e. false peaks) and wild points will randomly appear in the bearing history image, and even the target may be lost. Due to the influence of low ocean environmental noise and radiated noise of the detected target and other interference, the target trajectory is not obvious or even not displayed at all, which affects the correct detection and tracking of the target.

[0005] Therefore, in view of the limitations in processing the time bearing history graph in the passive sonar detection scene, a new processing method needs to be proposed to improve the accuracy of target detection. SUMMARY

[0006] The application provides an azimuth history trajectory enhancement method, a system, an electronic device and a storage medium, to solve the defects that the time-azimuth history graph cannot achieve better noise reduction effect and the target trajectory recognition is not accurate when a passive sonar detects a target in the prior art.

[0007] In a first aspect, the application provides an azimuth history trajectory enhancement method, comprising:

[0008] Obtaining several groups of array element channel receiving data in a hydrophone array in a plurality of preset time intervals;

[0009] Based on the several groups of array element channel receiving data, beamforming is performed to obtain a time-azimuth trajectory graph, and the time-azimuth trajectory graph is divided and binarized to obtain a plurality of binary azimuth trajectory graphs;

[0010] The connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of binary azimuth trajectory graphs are calculated, and based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, valid connected domains in the plurality of binary azimuth trajectory graphs are screened, and a plurality of target trajectory enhanced azimuth history graphs are obtained by fusing and splicing the screened plurality of binary azimuth trajectory graphs;

[0011] Extracting any adjacent first preset time interval and second preset time interval in the plurality of preset time intervals, merging the first target trajectory enhanced azimuth history graph corresponding to the first preset time interval and the second target trajectory enhanced azimuth history graph corresponding to the second preset time interval to generate a continuous time-azimuth history graph;

[0012] The duration of the first preset time interval is equal to the duration of the second preset time interval, and there is a partially repeated time period between the first preset time interval and the second preset time interval.

[0013] According to the azimuth history trajectory enhancement method provided by the application, the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of binary azimuth trajectory graphs are calculated, and based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, valid connected domains in the plurality of binary azimuth trajectory graphs are screened, and a plurality of target trajectory enhanced azimuth history graphs are obtained by fusing and splicing the screened plurality of binary azimuth trajectory graphs, comprising:

[0014] Obtaining a plurality of connected domains in each binary azimuth trajectory graph, calculating the connected domain area size of the plurality of connected domains and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of connected domains;

[0015] Based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, the valid connected domains in each binary azimuth trajectory graph are screened to obtain screened connected domains.

[0016] respectively, image morphological operation is performed on the screened connected domains in each binary azimuth trajectory image to obtain the plurality of target trajectory enhanced azimuth history images.

[0017] According to the azimuth history trajectory enhancement method provided by the application, the effective connected domains in each binary azimuth trajectory image are screened based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio to obtain screened connected domains, which comprises:

[0018] A connected domain area threshold is obtained, and if it is determined that the connected domain area size is greater than or equal to the connected domain area threshold, the connected domain corresponding to the connected domain area size is determined as a first effective connected domain.

[0019] A rectangle aspect ratio threshold is obtained, and if it is determined that the connected domain minimum circumscribed rectangle aspect ratio is less than the rectangle aspect ratio threshold, the connected domain corresponding to the connected domain minimum circumscribed rectangle aspect ratio is determined as a second effective connected domain.

[0020] The binary connected region that simultaneously satisfies the first effective connected domain and the second effective connected domain is taken as a screened binary connected region.

[0021] According to the azimuth history trajectory enhancement method provided by the application, the array channel receiving data of a plurality of groups of array elements in a plurality of preset time intervals is obtained, which comprises:

[0022] The frequency domain output beam of each group of array channel receiving data located at different azimuth angles is determined, wherein the array channel receiving data of each group is obtained in any preset time interval in the plurality of preset time intervals.

[0023] According to the azimuth history trajectory enhancement method provided by the application, the time azimuth trajectory image is obtained by beamforming based on the plurality of groups of array element channel receiving data, and the plurality of binary azimuth trajectory images is obtained by block binarization of the time azimuth trajectory image, which comprises:

[0024] The width energy integral is performed on the frequency domain output beam corresponding to each group of array element channel receiving data to obtain a plurality of azimuth history images.

[0025] The plurality of azimuth history images is divided into a plurality of local azimuth history images according to a preset step length.

[0026] Gaussian filtering and adaptive thresholding are sequentially performed on each local azimuth history image to obtain a plurality of binary trajectory block images.

[0027] The plurality of binary trajectory block images is spliced into the plurality of binary azimuth trajectory images according to the dimension size of the plurality of azimuth history images.

[0028] According to the azimuth history trajectory enhancement method provided by the application, the first target trajectory enhanced azimuth history graph corresponding to the first preset time interval and the second target trajectory enhanced azimuth history graph corresponding to the second preset time interval are merged to generate a continuous time azimuth history graph, which comprises the following steps:

[0029] The first preset time interval in the plurality of preset time intervals is acquired, and the second preset time interval adjacent to the first preset time interval is determined based on the first preset time interval;

[0030] The first target trajectory enhanced azimuth history graph corresponding to the first preset time interval is determined, and the second target trajectory enhanced azimuth history graph corresponding to the second preset time interval is determined;

[0031] The first target trajectory enhanced azimuth history graph and the second target trajectory enhanced azimuth history graph are connected, and the part of the repeated time period in the connection graph is removed to obtain the continuous time azimuth history graph.

[0032] In a second aspect, the application further provides an azimuth history trajectory enhancement system, which comprises:

[0033] A first generation module is configured to acquire channel receiving data of a plurality of groups of array elements in a hydrophone array in a plurality of preset time intervals;

[0034] A second generation module is configured to perform beam forming based on the channel receiving data of the plurality of groups of array elements to obtain a time azimuth trajectory graph, and to divide and binarize the time azimuth trajectory graph to obtain a plurality of binary azimuth trajectory graphs;

[0035] A calculation module is configured to calculate the area size of a connected domain and the length-width ratio of a minimum bounding rectangle of the connected domain of the plurality of binary azimuth trajectory graphs, and to filter valid connected domains in the plurality of binary azimuth trajectory graphs based on the area size of the connected domain and the length-width ratio of the minimum bounding rectangle of the connected domain, and to fuse and splice the filtered plurality of binary azimuth trajectory graphs to obtain a plurality of target trajectory enhanced azimuth history graphs;

[0036] A processing module is configured to extract a first preset time interval and a second preset time interval adjacent in the plurality of preset time intervals, and to merge a first target trajectory enhanced azimuth history graph corresponding to the first preset time interval and a second target trajectory enhanced azimuth history graph corresponding to the second preset time interval to generate a continuous time azimuth history graph;

[0037] The first preset time interval and the second preset time interval have equal time lengths, and the first preset time interval and the second preset time interval have a part of a repeated time period.

[0038] According to the azimuth history trajectory enhancement system provided by the application, the computing module comprises a computing submodule, a first screening submodule and an operation submodule, wherein:

[0039] The computing submodule is configured to acquire a plurality of connected domains in each binary azimuth trajectory graph, and calculate the connected domain area size of the plurality of connected domains and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of connected domains.

[0040] The first screening submodule is configured to screen the effective connected domains in each binary azimuth trajectory graph based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, and obtain screened connected domains.

[0041] The operation submodule is configured to perform image morphological operation on the screened connected domains in each binary azimuth trajectory graph respectively, and obtain the plurality of target trajectory enhancement azimuth history graphs.

[0042] In a third aspect, the application further provides an electronic device, which comprises a memory, a processor and a computer program stored in the memory and executable on the processor, and the processor implements the azimuth history trajectory enhancement method according to any one of the above aspects when executing the program.

[0043] The application further provides a non-transitory computer readable storage medium, which stores a computer program, and the computer program is executable on a processor to implement the azimuth history trajectory enhancement method according to any one of the above aspects.

[0044] The azimuth history trajectory enhancement method, system, electronic device and storage medium provided by the application can effectively enhance the contrast between the target and the background by performing background noise reduction and trajectory enhancement processing on the multi-target time azimuth history image of the passive sonar hydrophone, so that the extracted multi-target trajectory is clearer, and the display effect of the time azimuth history graph is improved. BRIEF DESCRIPTION OF DRAWINGS

[0045] In order to more clearly illustrate the technical solutions in the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0046] Figure 1 is a flowchart of the azimuth history trajectory enhancement method provided by the application;

[0047] Figure 2 is a structural schematic diagram of the azimuth history trajectory enhancement system provided by the application;

[0048] Figure 3 Figure 1 is a structural schematic diagram of an electronic device provided by the present application. DETAILED DESCRIPTION

[0049] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions in the present application will be described clearly and completely below with reference to the drawings in the present application. Obviously, the described embodiments are some but not all of the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of the present application.

[0050] The present application will be described below with reference to the drawings. Figures 1-3 The present application provides a bearing history trajectory enhancement method.

[0051] When a passive sonar performs target detection, a time bearing history graph of a detected target is usually processed to obtain the detected target. However, the time bearing history graph is often affected by environmental noise and radiation noise of the detected target, and strong background interference is easily generated, and the trajectory of the target cannot be clearly displayed, which greatly affects the effect of target detection and tracking. In view of the above problems, the present application proposes an effective background noise reduction and target trajectory enhancement processing for the time bearing history graph, and the specific implementation is as follows:

[0052] Figure 1 Figure 1 is a flow schematic diagram of the bearing history trajectory enhancement method provided by the present application, as shown in Figure 1, comprising: Figure 1

[0053] Step 100: acquiring several groups of array element channel receiving data in a hydrophone array in a plurality of preset time intervals;

[0054] Step 200: performing beam forming based on the several groups of array element channel receiving data to obtain a time bearing trajectory graph, and dividing and binarizing the time bearing trajectory graph into a plurality of binary bearing trajectory graphs;

[0055] Step 300: calculating the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of binary bearing trajectory graphs, screening the effective connected domains in the plurality of binary bearing trajectory graphs based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, and fusing and splicing the screened plurality of binary bearing trajectory graphs to obtain a plurality of target trajectory enhanced bearing history graphs;

[0056] ​Step 400: extracting any adjacent first preset time interval and second preset time interval in the plurality of preset time intervals, merging the first target trajectory enhanced bearing history graph corresponding to the first preset time interval and the second target trajectory enhanced bearing history graph corresponding to the second preset time interval to generate a continuous time bearing history graph;

[0057] The first preset time interval and the second preset time interval have equal time lengths, and the first preset time interval and the second preset time interval have a partially repeated time period.

[0058] It should be noted that the execution subject of the above method can be a computer device.

[0059] Specifically, in a certain short time interval, which is set as a first preset time interval, the channel receiving data of a plurality of array elements in a hydrophone array is extracted, and a short time bearing history image in the short time interval, i.e., a first bearing history graph, is obtained from the channel receiving data of the plurality of array elements.

[0060] The obtained first bearing history graph is subjected to image blocking and adaptive thresholding processing, i.e., the first bearing history graph is segmented into a plurality of small block images with equal step lengths, and the plurality of small block images are spliced to form a binary bearing trajectory graph with equal dimensions as the original first bearing history graph.

[0061] Further, the connected domain attribute value in the binary bearing trajectory graph, which is usually the connected domain contour area size or the aspect ratio of the minimum bounding rectangle of the connected domain, is used to remove the interference noise points of the time bearing history image, and morphological operation is used to smooth the effective trajectory region, so as to obtain a first target trajectory enhanced bearing history graph subjected to connected processing.

[0062] Similarly, another short time interval, i.e., a second preset time interval, is taken, and the time interval is equal to the first preset time interval and has a partially repeated time period. In the second preset time interval, a new cumulative bearing history graph is synthesized by overlapping the previous short time bearing history graph and the second preset time interval, and the above processing operation is repeated, so that the trajectories of the first preset time interval and the second preset time interval are coherent, a continuous time bearing history graph is formed, and the display effect of the time bearing history graph is improved as a whole.

[0063] The present application improves the display effect of the time bearing history graph by background noise reduction and potential target trajectory enhancement of the time bearing history graph in a complex underwater noise environment, so that the potential target trajectory is more easily discovered and tracked.

[0064] On the basis of the above embodiment, step 100 comprises:

[0065] The frequency domain output beams of each group of array element channel received data are determined, wherein the frequency domain output beams of each group of array element channel received data are obtained in any preset time interval of the plurality of preset time intervals.

[0066] Specifically, in a certain short time interval, set as time interval T, a plurality of array element channel received data in a hydrophone array are obtained, and the plurality of array element channel received data are subjected to frequency domain conventional beam forming at different azimuth angles.

[0067] The value of the certain short time interval needs to be moderate, too short will increase the calculation amount, too long will make the accumulated energy diverge, so that the target trajectory is not clear, and generally one beam forming per second can be performed. When the received data of each array element channel is subjected to frequency domain beam forming, the array element channel with relatively large gain is selected as much as possible, so that the signal-to-noise ratio of the received potential target is stronger, and the trajectory in the azimuth history diagram is clearer.

[0068] It should be further pointed out that the hydrophone array involved in the present application is generally an optical fiber hydrophone array, which is an underwater acoustic signal sensor based on optical fiber and optoelectronic technology. It converts underwater acoustic vibration into optical signal through high-sensitivity optical coherent detection, and transmits the optical signal to a signal processing system through an optical fiber to extract acoustic signal information. It has the characteristics of high sensitivity and good frequency response characteristics. Since optical fiber is used as an information carrier, it is suitable for long-distance and wide-range monitoring.

[0069] The present application can effectively enhance the signal-to-noise ratio of the target trajectory and enhance the clarity of the target trajectory by performing frequency domain beam forming on the azimuth history diagram of the short time interval.

[0070] On the basis of the above-mentioned embodiments, step 200 comprises:

[0071] The frequency domain output beams corresponding to each group of array element channel received data are subjected to width energy integration respectively, to obtain a plurality of azimuth history diagrams;

[0072] The plurality of azimuth history diagrams are divided into a plurality of local azimuth history diagrams according to a preset step size;

[0073] Each local azimuth history diagram is subjected to Gaussian filtering and adaptive thresholding processing in sequence respectively, to obtain a plurality of binary trajectory square images;

[0074] The plurality of binary trajectory square images are spliced into a plurality of binary azimuth trajectory images according to the dimension size of the plurality of azimuth history diagrams.

[0075] Specifically, on the basis of the foregoing embodiments, the result of conventional beam forming is subjected to width energy integration, to obtain the beam energy output at different azimuths in a certain short time interval, that is, a short-time azimuth history image at this time interval is obtained, which is defined as a first azimuth history diagram.

[0076] The obtained first orientation history image is segmented into multiple local images according to a certain step size, and the local images are respectively subjected to Gaussian filtering and adaptive thresholding to obtain a thresholded binary trajectory image, and each block is spliced into a complete binary trajectory image.

[0077] For example, the image is segmented into M small images of N*N according to an equal step size N, and the M small images are respectively subjected to Gaussian filtering and adaptive thresholding to obtain a thresholded binary trajectory image, and each block is spliced into a complete binary trajectory image, and the dimension size is restored to the dimension before processing.

[0078] It should be noted that the accumulated orientation history image is segmented into multiple small images and subjected to adaptive thresholding, so that the target trajectory in each small block area with relatively weak noise can be extracted. If the accumulated orientation history image is directly subjected to binaryzation, the gray difference between the target with relatively weak noise and the target with relatively strong noise is large, and after binaryzation, only the target trajectory with relatively strong noise is retained, and the target with relatively weak noise cannot be extracted, and part of the target information is easily lost.

[0079] The present application can identify target trajectories with large gray differences by segmenting the short-time orientation history image and then performing binaryzation, and can more completely retain target trajectory information.

[0080] On the basis of the above embodiment, step 300 comprises:

[0081] A plurality of connected domains in each binary orientation trajectory image are obtained, and the connected domain area size of the plurality of connected domains and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of connected domains are calculated.

[0082] Based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, the effective connected domain in each binary orientation trajectory image is screened to obtain a screened connected domain.

[0083] Image morphological operations are respectively performed on the screened connected domain in each binary orientation trajectory image to obtain a plurality of target trajectory enhanced orientation history images.

[0084] The screening of the effective connected domain in each binary orientation trajectory image based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio to obtain a screened connected domain comprises:

[0085] A connected domain area threshold is obtained, and if it is determined that the connected domain area size is greater than or equal to the connected domain area threshold, the connected domain corresponding to the connected domain area size is determined as a first effective connected domain.

[0086] The rectangular aspect ratio threshold is obtained, and if it is determined that the aspect ratio of the minimum bounding rectangle of the connected domain is less than the rectangular aspect ratio threshold, it is determined that the connected domain corresponding to the aspect ratio of the minimum bounding rectangle of the connected domain is a second effective connected domain;

[0087] The first effective connected domain and the second effective connected domain are connected to form the screened connected domain.

[0088] Optionally, in addition to the enhancement processing of the target trajectory, noise reduction processing is also needed for the background to eliminate noise interference as much as possible.

[0089] The area size and the aspect ratio of the minimum bounding rectangle of each connected domain of the binary direction trajectory image are calculated, the small-area noise point or wild point connected domain is filtered out by using the area size of the connected domain, the connected domain disturbed by the horizontal strip is filtered out by using the aspect ratio of the minimum bounding rectangle, and the closed operation of image morphology is performed on the remaining connected domain to fill and connect the local broken trajectory region, so that the trajectory boundary is relatively smooth and the trajectory region is relatively complete.

[0090] Specifically, after the image is binarized, a plurality of connected domains with different contour sizes are formed. When the area size of the connected domain accounts for greater than or equal to the connected domain area threshold C1, it is an effective trajectory region and the connected region is retained, otherwise it is a noise point and the connected region is filtered out. At the same time, considering that there may be horizontal straight line interference sometimes, the minimum bounding rectangle of each connected domain is calculated. When the aspect ratio of the rectangle is greater than the rectangular aspect ratio threshold C2, it is a horizontal disturbance and the connected region is not considered to be filtered out, otherwise it is an effective trajectory region and the connected region is retained. The retained connected region is subjected to the closed operation of image morphology, so that the local broken trajectory region is filled and connected, so that the trajectory boundary is relatively smooth and the trajectory region is relatively complete.

[0091] Here, when removing the interference noise points or wild points from the binary direction trajectory image, the area of the interference noise point or wild point connected domain is usually very small, the area ratio of the interference point or wild point connected domain to the small image area is relatively small, and the area ratio of the effective trajectory connected domain to the small image area is relatively large, so the area ratio of the connected domain can be used as a threshold to filter out small-area interference points. When removing the horizontal straight line interference, the horizontal distance of the minimum bounding rectangle of the horizontal strip interference connected domain is usually greater than the vertical distance, so the horizontal and vertical distance ratio of the minimum bounding rectangle of the connected domain can be used as a threshold to filter out the horizontal strip interference. When smoothing the effective trajectory region, the effective trajectory region may be relatively close but not connected. The morphological closing operation can suture the discontinuous trajectory to make the trajectory region sutured and connected, and also make the trajectory around more smooth.

[0092] The application improves the display effect of the course graph of the accumulated time by performing connected domain processing on the binary direction trajectory graph, removing most of the background interference while retaining the effective trajectory area, and enhancing the target trajectory.

[0093] On the basis of the above embodiment, step 400 comprises:

[0094] The first preset time interval is obtained from the plurality of preset time intervals, and the second preset time interval adjacent to the first preset time interval is determined based on the first preset time interval.

[0095] The first target trajectory enhanced direction course graph corresponding to the first preset time interval is determined, and the second target trajectory enhanced direction course graph corresponding to the second preset time interval is determined.

[0096] The first target trajectory enhanced direction course graph and the second target trajectory enhanced direction course graph are connected, and the part of the repeated time period in the connected graph is removed to obtain the continuous time direction course graph.

[0097] Optionally, on the basis of obtaining the first target trajectory enhanced direction course graph, the second preset time interval T is compared with the first preset time interval T, and a new time direction course graph is generated by accumulation again.

[0098] After the time of T seconds is accumulated again, the direction course graph array at this moment is obtained, and the direction course graph is overlapped with the direction course graph accumulated last time for several seconds to synthesize a new time direction graph array, and the image blocking, adaptive thresholding and connected domain operation are repeated to improve the display effect of the time direction course graph as a whole.

[0099] Here, the two target trajectory enhanced direction course graphs are synthesized into a continuous time direction course graph, so that the two short time periods of the two accumulated time direction graphs are overlapped, the direction trajectories of the two time periods are relatively continuous, and when the fast-changing target appears, the trajectories of the two accumulated direction course graphs are not discontinuous and disconnected.

[0100] The application repeatedly generates the target trajectory enhanced direction course graph of the same time interval, and performs merging processing with the original target trajectory enhanced direction course graph, thereby effectively ensuring the continuity of the target trajectory, and having strong adaptability in the fast-changing target scene.

[0101] The direction course trajectory enhancement system provided by the application is described below, and the direction course trajectory enhancement system described below can be correspondingly referred to the direction course trajectory enhancement method described above.

[0102] Figure 2 is a structural schematic diagram of the direction course trajectory enhancement system provided by the application, like Figure 2As shown, comprising: a first generation module 21, a second generation module 22, a calculation module 23 and a processing module 24, wherein:

[0103] The first generation module 21 is used for acquiring a plurality of groups of array element channel receiving data in a plurality of preset time intervals; the second generation module 22 is used for performing beamforming based on the plurality of groups of array element channel receiving data to obtain a time-azimuth track diagram, and binarizing the time-azimuth track diagram to obtain a plurality of binary azimuth track diagrams; the calculation module 23 is used for calculating the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of binary azimuth track diagrams, screening the valid connected domains in the plurality of binary azimuth track diagrams based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, and fusing and splicing the screened plurality of binary azimuth track diagrams to obtain a plurality of target track enhanced azimuth history diagrams; and the processing module 24 is used for extracting any adjacent first preset time interval and second preset time interval in the plurality of preset time intervals, merging the first target track enhanced azimuth history diagram corresponding to the first preset time interval and the second target track enhanced azimuth history diagram corresponding to the second preset time interval to generate a continuous time-azimuth history diagram; wherein the time length of the first preset time interval is equal to that of the second preset time interval, and there is a partial repeated time period between the first preset time interval and the second preset time interval.

[0104] The present application improves the display effect of the time-azimuth history diagram by background noise reduction and potential target track enhancement in the complex underwater noise environment, so that the potential target track is more easily discovered and tracked.

[0105] On the basis of the above-mentioned embodiments, the first generation module 21 is specifically used for:

[0106] Determining the frequency domain output beam of each group of array element channel receiving data located at different azimuth angles, wherein the each group of array element channel receiving data is acquired in any preset time interval in the plurality of preset time intervals.

[0107] The present application can effectively enhance the signal-to-noise ratio of the target track and enhance the clarity of the target track by performing frequency domain beamforming on the azimuth history diagram of a short time interval.

[0108] On the basis of the above-mentioned embodiments, the second calculation module 22 comprises an integration sub-module 221, a segmentation sub-module 222, a binary processing sub-module 223 and a splicing sub-module 224, wherein:

[0109] The integral sub-module 221 is configured to perform width energy integration on the frequency domain output beams corresponding to the received data of each group of array element channels respectively to obtain a plurality of azimuth profiles; the segmentation sub-module 222 is configured to segment the plurality of azimuth profiles into a plurality of local azimuth profiles according to a preset step length; the binary processing sub-module 223 is configured to sequentially perform Gaussian filtering and adaptive thresholding processing on each local azimuth profile to obtain a plurality of binary trajectory square images; and the splicing sub-module 224 is configured to splice the plurality of binary trajectory square images into the plurality of binary azimuth trajectory images according to the dimension size of the plurality of azimuth profiles.

[0110] The present application can identify target trajectories with large gray scale differences by segmenting the short-time azimuth profile and then performing binaryzation, and can more completely retain target trajectory information.

[0111] On the basis of the above embodiment, the calculation module 23 comprises a calculation sub-module 231, a first screening sub-module 232 and an operation sub-module 233, wherein:

[0112] The calculation sub-module 231 is configured to obtain a plurality of connected domains in each binary azimuth trajectory image, and calculate the connected domain area size of the plurality of connected domains and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of connected domains; the first screening sub-module 232 is configured to screen the effective connected domains in each binary azimuth trajectory image based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio to obtain screened connected domains; and the operation sub-module 233 is configured to perform image morphological operation on the screened connected domains in each binary azimuth trajectory image to obtain the plurality of target trajectory enhanced azimuth profiles.

[0113] The screening sub-module 232 is specifically configured to obtain a connected domain area threshold value, and determine that the connected domain corresponding to the area size is a first effective connected domain if it is determined that the connected domain area size is greater than or equal to the connected domain area threshold value; obtain a rectangle aspect ratio threshold value, and determine that the connected domain corresponding to the minimum circumscribed rectangle aspect ratio is a second effective connected domain if it is determined that the connected domain minimum circumscribed rectangle aspect ratio is less than the rectangle aspect ratio threshold value; and take the binary connected domain that simultaneously satisfies the first effective connected domain and the second effective connected domain as the screened binary connected domain.

[0114] The present application performs connected domain processing on the binary azimuth trajectory image, removes most of the background interference while retaining the effective trajectory area, and enhances the target trajectory, thereby improving the profile display effect of the segment of cumulative time.

[0115] On the basis of the above embodiment, the processing module 24 comprises a first determination sub-module 241, a second determination sub-module 242 and a connection sub-module 243, wherein:

[0116] The first determining submodule 241 is configured to acquire the first preset time interval from the plurality of preset time intervals, and determine the adjacent second preset time interval based on the first preset time interval. The second determining submodule 242 is configured to determine the first target trajectory enhanced bearing history graph corresponding to the first preset time interval, and determine the second target trajectory enhanced bearing history graph corresponding to the second preset time interval. The connecting submodule 243 is configured to connect the first target trajectory enhanced bearing history graph and the second target trajectory enhanced bearing history graph, and remove the part of the repeated time period in the connection graph to obtain the continuous time bearing history graph.

[0117] The application effectively ensures the continuity of the target trajectory by repeatedly generating the target trajectory enhanced bearing history graph of the same time interval and merging the target trajectory enhanced bearing history graph with the original target trajectory enhanced bearing history graph, and has strong adaptability in the fast-changing target scene.

[0118] Figure 3 An example of an entity structure diagram of an electronic device is shown in Figure 3 As shown in the figure, the electronic device can include a processor 310, a communications interface 320, a memory 330, and a communications bus 340, wherein the processor 310, the communications interface 320, and the memory 330 complete mutual communication through the communications bus 340. The processor 310 can call the logical instructions in the memory 330 to execute the bearing history trajectory enhancement method, which includes: acquiring several groups of array element channel receiving data in a hydrophone array in a plurality of preset time intervals; based on the several groups of array element channel receiving data, performing beam forming to obtain a time bearing trajectory graph, and binarizing the time bearing trajectory graph to obtain a plurality of binary bearing trajectory graphs; calculating the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of binary bearing trajectory graphs, and screening the valid connected domains in the plurality of binary bearing trajectory graphs based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio; fusing and splicing the screened plurality of binary bearing trajectory graphs to obtain a plurality of target trajectory enhanced bearing history graphs; extracting any adjacent first preset time interval and second preset time interval from the plurality of preset time intervals, merging the first target trajectory enhanced bearing history graph corresponding to the first preset time interval with the second target trajectory enhanced bearing history graph corresponding to the second preset time interval to generate a continuous time bearing history graph; wherein the time length of the first preset time interval is equal to the time length of the second preset time interval, and the first preset time interval and the second preset time interval have a part of the repeated time period.

[0119] Moreover, the logic instructions in the memory 330 described above can be implemented in the form of software functional units and sold or used as independent products, and can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application essentially or the parts that make contributions to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0120] In another aspect, the present application also provides a computer program product, which comprises a computer program, the computer program can be stored on a non-transitory computer readable storage medium, and the computer program can be executed by a processor to enable a computer to perform the bearing history trajectory enhancement method provided by the above-mentioned methods. The method comprises: acquiring channel receiving data of a plurality of groups of array elements in a hydrophone array in a plurality of preset time intervals; performing beamforming based on the channel receiving data of the plurality of groups of array elements to obtain a time bearing trajectory graph, and binarizing the time bearing trajectory graph to obtain a plurality of binary bearing trajectory graphs; calculating the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of binary bearing trajectory graphs, screening valid connected domains in the plurality of binary bearing trajectory graphs based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, and fusing and splicing the screened plurality of binary bearing trajectory graphs to obtain a plurality of target trajectory enhancement bearing history graphs; extracting any adjacent first preset time interval and second preset time interval in the plurality of preset time intervals, merging the first target trajectory enhancement bearing history graph corresponding to the first preset time interval and the second target trajectory enhancement bearing history graph corresponding to the second preset time interval to generate a continuous time bearing history graph; wherein the time length of the first preset time interval is equal to the time length of the second preset time interval, and there is a partially overlapping time period between the first preset time interval and the second preset time interval.

[0121] In yet another aspect, the present application also provides a non-transitory computer readable storage medium having stored thereon a computer program, which, when executed by a processor, implements the bearing track enhancement method provided by any of the above methods, and the method comprises: acquiring channel receiving data of a plurality of groups of array elements in a hydrophone array in a plurality of preset time intervals; performing beamforming based on the channel receiving data of the plurality of groups of array elements to obtain a time bearing track diagram, and binarizing the time bearing track diagram to obtain a plurality of binary bearing track diagrams; calculating the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio of the plurality of binary bearing track diagrams, screening valid connected domains in the plurality of binary bearing track diagrams based on the connected domain area size and the connected domain minimum circumscribed rectangle aspect ratio, and fusing and splicing the screened plurality of binary bearing track diagrams to obtain a plurality of target track enhancement bearing track diagrams; extracting any adjacent first preset time interval and second preset time interval in the plurality of preset time intervals, merging a first target track enhancement bearing track diagram corresponding to the first preset time interval and a second target track enhancement bearing track diagram corresponding to the second preset time interval to generate a continuous time bearing track diagram; wherein the first preset time interval and the second preset time interval have equal time lengths, and the first preset time interval and the second preset time interval have a partially overlapping time period.

[0122] The device embodiments described above are merely illustrative, wherein the units illustrated as separate components can or can not be physically separated, and the components illustrated as units can or can not be physical units, i.e., can be located in one place or distributed on multiple network units. Part or all of the modules can be selected to achieve the purpose of the embodiment scheme according to actual needs. Those skilled in the art can understand and implement without creative labor.

[0123] From the above description of the embodiments, those skilled in the art can clearly understand that the embodiments can be implemented by means of software plus necessary universal hardware platforms, and of course can also be implemented by hardware. Based on such understanding, the above technical solutions, essentially or in terms of the contribution to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer readable storage medium, such as a ROM / RAM, a magnetic disk, an optical disk, etc., and includes a plurality of instructions to make a computer device (which can be a personal computer, a server, or a network device, etc.) execute the methods described in each embodiment or some parts of the embodiments.

[0124] It should be pointed out finally that the above embodiments are only used to illustrate the technical solutions of the present application, but not to limit the same; and although the present application has been described in detail with reference to the foregoing embodiments, it should be appreciated by those skilled in the art that the technical solutions recorded in the foregoing embodiments can be modified, or some technical features thereof can be replaced equivalently; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for enhancing orientation history trajectories, characterized in that, include: Acquire data received from several array element channels in a hydrophone array within multiple preset time intervals; Based on the received data from the aforementioned array element channels, beamforming is performed to obtain a time azimuth trajectory map, and the time azimuth trajectory map is divided into blocks and binarized to obtain multiple binary azimuth trajectory maps. Calculate the area of ​​the connected components and the aspect ratio of the minimum bounding rectangle of the connected components in the multiple binary azimuth trajectory maps. Based on the area of ​​the connected components and the aspect ratio of the minimum bounding rectangle of the connected components, filter the effective connected components in the multiple binary azimuth trajectory maps. Then, merge and stitch the filtered multiple binary azimuth trajectory maps to obtain multiple target trajectory enhanced azimuth history maps. Extract any adjacent first and second preset time intervals from the plurality of preset time intervals, and merge the first target trajectory enhanced azimuth history map corresponding to the first preset time interval with the second target trajectory enhanced azimuth history map corresponding to the second preset time interval to generate a continuous time azimuth history map. Wherein, the first preset time interval and the second preset time interval have the same duration, and there is a partial overlap between the first preset time interval and the second preset time interval; The process involves calculating the area of ​​connected components and the aspect ratio of the minimum bounding rectangle of the connected components in the multiple binary azimuth trajectory maps. Based on these factors, effective connected components are selected from the multiple binary azimuth trajectory maps. The selected binary azimuth trajectory maps are then merged and stitched together to obtain multiple target trajectory enhanced azimuth history maps, including: Obtain multiple connected components in each binary orientation trajectory map, and calculate the area of ​​each connected component and the aspect ratio of the minimum bounding rectangle of each connected component. Based on the area of ​​the connected component and the aspect ratio of the minimum bounding rectangle of the connected component, the effective connected components in each binary azimuth trajectory map are filtered to obtain the filtered connected components. Image morphology operations are performed on the filtered connected components in each binary azimuth trajectory map to obtain the enhanced azimuth history map of the multiple target trajectories. The process of filtering the effective connected components in each binary orientation trajectory map based on the area of ​​the connected component and the aspect ratio of the minimum bounding rectangle of the connected component to obtain the filtered connected components includes: Obtain a connected component area threshold. If it is determined that the size of the connected component area is greater than or equal to the connected component area threshold, then the connected component corresponding to the size of the connected component area is determined to be the first valid connected component. Obtain the rectangle aspect ratio threshold. If it is determined that the aspect ratio of the minimum bounding rectangle of the connected component is less than the rectangle aspect ratio threshold, then the connected component corresponding to the aspect ratio of the minimum bounding rectangle of the connected component is determined to be the second valid connected component. Binary connected regions that simultaneously satisfy both the first and second valid connected regions are selected as the filtered binary connected regions.

2. The orientation history trajectory enhancement method according to claim 1, characterized in that, The acquisition of received data from several array element channels in the hydrophone array within multiple preset time intervals includes: The frequency domain output beams at different azimuth angles are determined for the received data of each group of array element channels, wherein the received data of each group of array element channels is acquired within any preset time interval among the plurality of preset time intervals.

3. The orientation history trajectory enhancement method according to claim 2, characterized in that, The process of receiving data from the aforementioned array element channels, performing beamforming to obtain a time-azimuth trajectory map, and then binarizing the time-azimuth trajectory map into blocks to obtain multiple binary azimuth trajectory maps includes: By performing width energy integration on the frequency domain output beam corresponding to the received data of each group of array element channels, multiple azimuth history maps are obtained. The multiple azimuth history maps are divided into several local azimuth history maps according to a preset step size; Gaussian filtering and adaptive thresholding were applied to each local orientation history map in sequence to obtain multiple binary trajectory block images; Based on the dimensionality of the plurality of orientation history maps, the plurality of binary trajectory block images are stitched together to form the plurality of binary orientation trajectory maps.

4. The orientation history trajectory enhancement method according to claim 1, characterized in that, The step of extracting any adjacent first and second preset time intervals from the plurality of preset time intervals, and merging the first target trajectory enhanced azimuth history map corresponding to the first preset time interval with the second target trajectory enhanced azimuth history map corresponding to the second preset time interval to generate a continuous time azimuth history map includes: Obtain the first preset time interval from the plurality of preset time intervals, and determine the adjacent second preset time intervals based on the first preset time interval; Determine the enhanced azimuth history map of the first target trajectory corresponding to the first preset time interval, and determine the enhanced azimuth history map of the second target trajectory corresponding to the second preset time interval; By connecting the first target trajectory enhanced azimuth history map and the second target trajectory enhanced azimuth history map, and removing the overlapping time periods in the connecting map, the continuous time azimuth history map is obtained.

5. A location history trajectory enhancement system, characterized in that, include: The first generation module is used to acquire the received data of several array element channels in the hydrophone array within multiple preset time intervals; The second generation module is used to perform beamforming to obtain a time azimuth trajectory map based on the received data from the several sets of array element channels, and to divide the time azimuth trajectory map into blocks and binarize it to obtain multiple binary azimuth trajectory maps. The calculation module is used to calculate the area of ​​the connected components and the aspect ratio of the minimum bounding rectangle of the connected components in the multiple binary azimuth trajectory maps. Based on the area of ​​the connected components and the aspect ratio of the minimum bounding rectangle of the connected components, the effective connected components in the multiple binary azimuth trajectory maps are selected. The selected multiple binary azimuth trajectory maps are then merged and stitched together to obtain multiple target trajectory enhanced azimuth history maps. The processing module is used to extract any adjacent first preset time interval and second preset time interval from the plurality of preset time intervals, and merge the first target trajectory enhanced azimuth history map corresponding to the first preset time interval and the second target trajectory enhanced azimuth history map corresponding to the second preset time interval to generate a continuous time azimuth history map. Wherein, the first preset time interval and the second preset time interval have the same duration, and there is a partial overlap between the first preset time interval and the second preset time interval; The calculation module includes a calculation submodule, a first filtering submodule, and an operation submodule, wherein: The calculation submodule is used to obtain multiple connected components in each binary orientation trajectory map, and calculate the area of ​​the multiple connected components and the aspect ratio of the minimum bounding rectangle of the multiple connected components. The first filtering submodule is used to filter the effective connected components in each binary directional trajectory map based on the area size of the connected component and the aspect ratio of the minimum bounding rectangle of the connected component, and obtain the filtered connected components. The operation submodule is used to perform image morphology operations on the filtered connected components in each binary azimuth trajectory map to obtain the enhanced azimuth history map of the multiple target trajectories. The first filtering submodule is specifically used for: Obtain a connected component area threshold. If it is determined that the size of the connected component area is greater than or equal to the connected component area threshold, then the connected component corresponding to the size of the connected component area is determined to be the first valid connected component. Obtain the rectangle aspect ratio threshold. If it is determined that the aspect ratio of the minimum bounding rectangle of the connected component is less than the rectangle aspect ratio threshold, then the connected component corresponding to the aspect ratio of the minimum bounding rectangle of the connected component is determined to be the second valid connected component. Binary connected regions that simultaneously satisfy both the first and second valid connected regions are selected as the filtered binary connected regions.

6. 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 orientation history trajectory enhancement method as described in any one of claims 1 to 4.

7. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the orientation history trajectory enhancement method as described in any one of claims 1 to 4.

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