Large aperture array near field target fast passive direction finding and ranging method and system

Abstract

This invention provides a rapid passive direction finding and ranging method and system for near-field targets using a large-aperture array, relating to the fields of underwater acoustic detection and array signal processing. The method includes: acquiring the target array; calculating the theoretical main lobe width of the array based on the array's natural directivity formula; extracting the measured bandwidth (-3dB) of the spatial spectrum from the received array signal; and comparing the measured bandwidth with a threshold multiple of the theoretical beamwidth to initially determine the target's near-field and far-field characteristics. If determined to be a near-field target, the original array is iteratively divided into subarrays using a bisection method, repeating the subarray beamwidth comparison and verification process until the threshold condition is met. The near-field and far-field critical distances are then calculated based on the aperture inversion of the convergent subarrays, and a small-range near-field focusing scan is performed. The target's optimal azimuth and range parameters are locked at the narrowest beamwidth value, completing the full-space near-field focusing scan and generating a target azimuth history map and range tracking curve. This invention achieves rapid and high-precision passive direction finding and ranging of near-field targets under large-aperture conditions.

Description

Technical Field

[0001] This invention relates to the field of underwater acoustic detection and array signal processing technology, and more specifically, to a method and system for rapid passive direction finding and ranging of near-field targets with a large aperture array. Background Technology

[0002] Currently, to improve space processing performance, modern sonar systems are developing towards large-scale, large-aperture arrays. Increasing the array aperture relative to the target distance can significantly improve array gain and azimuth resolution for far-field targets. However, the increased aperture also significantly expands the array's near-field spatial coverage. Near-field target wavefronts exhibit spherical wave characteristics, no longer satisfying the far-field plane wave assumption. If the far-field compensation model is continued for azimuth estimation, it will lead to a decrease in array gain and a deterioration in direction-finding performance. Therefore, a near-field compensation model must be adopted, and near-field discrimination has become a key issue in large-aperture array detection.

[0003] Existing near-field passive positioning technologies mostly employ full-domain two-dimensional spatial scanning to achieve target localization, which suffers from high computational load and poor real-time performance. Some subarray-based methods are primarily used for interference suppression and do not address near-field discrimination and coarse distance measurement to achieve efficient hierarchical positioning. While high-resolution methods for mixed near-field sources offer high positioning accuracy, they lack a fast near-field discrimination mechanism, making it impossible to achieve low-complexity and rapid near-field target direction finding and ranging under large-aperture arrays. This makes it difficult to meet the requirements of both real-time performance and high accuracy in engineering applications. Summary of the Invention

[0004] The problem solved by this invention is how to achieve rapid and high-precision passive direction finding and ranging of near-field targets under large aperture conditions.

[0005] To address the aforementioned problems, this invention provides a method, system, electronic device, and storage medium for rapid passive direction finding and ranging of near-field targets using a large aperture array.

[0006] In a first aspect, the present invention provides a method for rapid passive direction finding and ranging of near-field targets using a large-aperture array, comprising:

[0007] Obtain the target array, and based on the array's natural directivity calculation formula, obtain the theoretical main lobe width of the target array;

[0008] The received signal of the target array is processed by far-field beamforming to obtain a spatial spectrum, and the measured bandwidth of the target array is extracted based on the spatial spectrum.

[0009] The measured bandwidth is compared with k times the theoretical main lobe width. If the measured bandwidth is less than or equal to k times the theoretical main lobe width, the target array is located in the far field, and the azimuth spectrum result is output. If the measured bandwidth of the target array is greater than k times the theoretical main lobe width, the target array is divided into two sub-arrays, the theoretical far-field beamwidth of the two sub-arrays is calculated, and the received signal of the sub-arrays is processed by far-field beamforming to obtain the actual spectral peak width.

[0010] Obtain the theoretical beamwidth, compare the actual spectral peak width with the theoretical beamwidth. If the actual spectral peak width is greater than k times the theoretical beamwidth, divide the current subarray into 2 new subarrays and repeat the process until it is less than k times the theoretical beamwidth. If the actual spectral peak width is less than or equal to k times the theoretical beamwidth, obtain the near-field and far-field critical distances based on the aperture of the current subarray.

[0011] Centered on the near and far field critical distance, a near field focusing scan is performed within a preset range. The output beamwidth at different distances is compared, and the azimuth and distance values ​​corresponding to the narrowest beam are taken. Based on the azimuth and distance values, a near field focusing scan is performed to obtain the azimuth history map and distance tracking curve of the target array.

[0012] Optionally, obtaining the target array, based on the array's natural directivity calculation formula, to obtain the theoretical main lobe width of the target array, includes:

[0013] The target array is obtained, and the theoretical main lobe width of the target array is obtained based on the array's natural directivity calculation formula. ,

[0014] In the formula, θ DT The theoretical main lobe width of the target array is given by M, where M is the number of array elements and d is the element spacing. Let θ be the signal wavelength. p Let K be the incident azimuth angle of the target array, and K be a preset angle conversion constant.

[0015] Furthermore, the specific steps of the array natural directivity calculation formula include:

[0016] Obtain the target array, construct an array coordinate system with east as the x-axis and north as the y-axis, and define the target azimuth as an angle of north-east. Based on the incident azimuth of the p-th target... The target array is presumably configured so that each element receives a far-field plane wave with the same frequency, phase, and amplitude. The directivity function of the target array is determined based on the phase difference between adjacent elements. ,

[0017] In the formula, M is the number of array elements, and d is the spacing between array elements. The signal wavelength is and satisfies =c / f, where c is the speed of sound in water, f is the signal frequency, and θ p The incident azimuth angle of the target array;

[0018] Combining the theory of natural directivity of arrays, and taking the amplitude of the directivity function decreasing to a preset decibel as the criterion for determining the half-power point, the derivation is simplified by substituting the normal incident direction of the target array.

[0019] The formula for calculating the natural directivity of the array was determined. .

[0020] Optionally, the step of performing far-field beamforming processing on the received signal of the target array to obtain a spatial spectrum, and extracting the measured bandwidth of the target array based on the spatial spectrum, includes:

[0021] The received signal is scanned using a far-field beamforming method. Inside, obtain the peak search function. ,as follows:

[0022] ,

[0023] Where θ is the spatial observation azimuth angle, p(θ) is the spectral peak search function, a(θ) is the array manifold steering vector corresponding to the θ direction, H is the conjugate transpose operation, and R is the data covariance matrix of the received signal;

[0024] Calculate the spatial spectral power at each angle based on the peak search function and plot the spatial spectrum.

[0025] Based on the spatial spectrum, locate the peak position of the spectrum peak and extract the angles of the left and right half-power points corresponding to a preset decibel decrease in peak power. and The measured bandwidth is obtained based on the difference between the two values, as follows:

[0026] .

[0027] Optionally, the near-field and far-field critical distances obtained based on the aperture of the current sub-array... ,

[0028] In the formula, L is the aperture of the sub-array, λ is the signal wavelength, and α is the empirical adjustment parameter for the near-field boundary. Centered on.

[0029] Optionally, the step of performing near-field focusing scanning within a preset range, centered on the near-field and far-field critical distance, comparing the output beamwidth at different distances, and taking the azimuth and distance values ​​corresponding to the narrowest beam, includes:

[0030] Centered on the near-far field critical distance, with the lower boundary taken as 0.25 times the near-far field critical distance and the upper boundary taken as 4 times the near-far field critical distance, a preset range r∈[ , ], where L is the aperture of the subarray and λ is the signal wavelength;

[0031] Near-field focusing scanning is performed within the preset range with a preset scanning step size. The output beamwidth at different distances is compared, and the azimuth and distance values ​​corresponding to the narrowest beam are taken.

[0032] Optionally, the step of performing a near-field focusing scan based on the azimuth and the distance value to obtain the azimuth history map and range tracking curve of the target array includes:

[0033] Based on the azimuth and the distance value, a near-field focusing scan is performed to obtain a full-angle azimuth spectrum. The current time slice in the azimuth history map is updated based on the azimuth spectrum to obtain the azimuth history map and distance tracking curve of the target array.

[0034] Secondly, the large-aperture array near-field target rapid passive direction finding and ranging system of the present invention includes:

[0035] The data acquisition unit is used to acquire the target array and obtain the theoretical main lobe width of the target array based on the array's natural directivity calculation formula.

[0036] The data extraction unit is used to perform far-field beamforming processing on the received signal of the target array to obtain a spatial spectrum, and extract the measured bandwidth of the target array based on the spatial spectrum;

[0037] The data analysis unit is used to compare the measured bandwidth with k times the theoretical main lobe width. If the measured bandwidth is less than or equal to k times the theoretical main lobe width, the target array is located in the far field, and the azimuth spectrum result is output. If the measured bandwidth of the target array is greater than k times the theoretical main lobe width, the target array is divided into two sub-arrays, the theoretical far-field beamwidth of the two sub-arrays is calculated, and the received signal of the sub-arrays is processed by far-field beamforming to obtain the actual spectral peak width.

[0038] The data analysis unit is also used to obtain the theoretical beamwidth, compare the actual spectral peak width with the theoretical beamwidth, and if the actual spectral peak width is greater than k times the theoretical beamwidth, then the current subarray is divided into 2 new subarrays, and the process is repeated until it is less than k times the theoretical beamwidth; if the actual spectral peak width is less than or equal to k times the theoretical beamwidth, the near-field and far-field critical distances are obtained based on the aperture of the current subarray.

[0039] The data processing unit is used to perform near-field focusing scans within a preset range with the near-field and far-field critical distances as the center, compare the output beamwidths at different distances, take the azimuth and distance values ​​corresponding to the narrowest beam, and perform a near-field focusing scan based on the azimuth and distance values ​​to obtain the azimuth history map and distance tracking curve of the target array.

[0040] Thirdly, the electronic device of the present invention includes: a processor and a memory, the memory being used to store a computer program;

[0041] When the computer program is loaded by the processor, it causes the processor to execute the above-described fast passive orientation and ranging method for near-field targets with a large aperture array.

[0042] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method for rapid passive orientation and ranging of near-field targets with a large aperture array.

[0043] This invention discloses a method, system, electronic device, and storage medium for rapid passive direction finding and ranging of near-field targets using a large-aperture array. First, it derives the theoretical main lobe width based on the array's natural directivity. Simultaneously, it performs far-field beamforming on the received array signal and extracts the measured -3dB bandwidth of the spatial spectrum. By comparing the measured beamwidth with a threshold multiple of the theoretical beamwidth, it achieves rapid near-field and far-field initial discrimination. This eliminates the need for complex two-dimensional traversal across the entire domain, directly determining the target's location and avoiding the array gain attenuation and large direction finding deviations caused by directly using far-field models to handle near-field targets. For targets identified as near-field, this invention employs a hierarchical bisectioning and iterative discrimination strategy. By continuously segmenting the subarrays and comparing and verifying their apertures, it gradually converges to subarrays that meet the threshold conditions. The near-field and far-field critical distances are then calculated based on the aperture of the qualified subarrays. This hierarchical iterative discrimination method replaces the traditional two-dimensional global range-angle joint scanning of the entire array, significantly reducing the computational dimensionality and data processing volume, lowering algorithm complexity, and improving real-time performance. A hierarchical positioning system is constructed, consisting of initial overall array assessment, iterative subarray subdivision, and critical distance calculation. This system eliminates the need for complex high-resolution parameter estimation, relying solely on beamwidth differences to distinguish near and far fields and calibrate critical distances, thus adapting to rapid near-field target differentiation in large-aperture arrays. After calculating the near and far field critical distances, a small-range near-field focusing scan is performed centered on these critical distances. The parameters corresponding to the minimum beamwidth are used as the optimal distance and target azimuth. Based on the optimal distance, full-space near-field focusing beamforming is then completed, updating the azimuth history slices and generating azimuth history maps and range tracking curves. This approach reduces the scanning range while maintaining ranging and direction-finding accuracy, accommodating the engineering application requirements of rapid processing, low computational load, and high-precision positioning and tracking in large-aperture array scenarios. Attached Figure Description

[0044] Figure 1 This is a flowchart illustrating the rapid passive direction finding and ranging method for near-field targets using a large aperture array, as described in this embodiment of the invention.

[0045] Figure 2 This is a flowchart of the fast passive direction finding and ranging method for near-field targets with a large aperture array in an embodiment of the present invention.

[0046] Figure 3 This is a schematic diagram of the natural directivity of a conventional beamforming array in an embodiment of the present invention;

[0047] Figure 4 This is a comparison diagram of the azimuth spectrum results of focusing scans on a 1km near-field target at different distances in an embodiment of the present invention;

[0048] Figure 5 This is a diagram showing the far-field orientation history measurement results of a near-field target moving in a straight line from 1km to 4km in an embodiment of the present invention.

[0049] Figure 6This is a schematic diagram of the process of dividing a 1km near-field target subarray in an embodiment of the present invention;

[0050] Figure 7 This is the precise measurement result of the azimuth and distance of a near-field target at 1km in this embodiment of the invention;

[0051] Figure 8 This is a diagram showing the azimuth history result after azimuth spectrum replacement in an embodiment of the present invention;

[0052] Figure 9 This is a diagram showing the ranging results of a moving target in an embodiment of the present invention. Detailed Implementation

[0053] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Although some embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided to provide a more thorough and complete understanding of the present invention. It should be understood that the accompanying drawings and embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of protection of the present invention.

[0054] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. Furthermore, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0055] The term "comprising" and its variations as used herein are open-ended, meaning "including but not limited to"; the term "based on" means "at least partially based on"; the term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments"; and the term "optionally" means "optional embodiments". Definitions of other terms will be given in the following description. It should be noted that the concepts of "first," "second," etc., mentioned in this invention are used only to distinguish different devices, modules, or units, and are not intended to limit the order of functions performed by these devices, modules, or units or their interdependencies.

[0056] It should be noted that the terms "one" and "more" used in this invention are illustrative rather than restrictive. Those skilled in the art should understand that, unless otherwise expressly indicated in the context, they should be understood as "one or more".

[0057] The names of the messages or information exchanged between the multiple devices in the embodiments of the present invention are for illustrative purposes only and are not intended to limit the scope of these messages or information.

[0058] In related technologies, to improve spatial processing performance, modern sonar systems are developing towards large-scale, large-aperture arrays. Increasing the array aperture relative to the target distance significantly improves the array gain and azimuth resolution for far-field targets, laying the foundation for accurate detection. However, the increased aperture also significantly expands the array's near-field spatial coverage. Near-field target wavefronts exhibit spherical wave characteristics, no longer satisfying the far-field plane wave assumption. If the far-field compensation model is continued for azimuth estimation, it will lead to a decrease in array gain, deterioration of direction-finding performance, and even problems such as excessive positioning deviation and target identification failure. Therefore, a near-field compensation model must be adopted. Near-field discrimination has become a key issue in large-aperture array detection, directly determining the positioning accuracy and operational reliability of the detection system.

[0059] Furthermore, the implementation schemes of traditional near-field passive positioning technologies are severely mismatched with the engineering application requirements of large-aperture arrays, leading to multiple technical bottlenecks. Existing near-field passive positioning technologies mostly employ full-domain two-dimensional spatial scanning for target localization, requiring simultaneous traversal of both distance and angle dimensions. The data processing volume per scan is extremely large, resulting in low computational efficiency and poor real-time performance, making it difficult to meet the core requirement of rapid detection in large-aperture arrays. Some methods based on subarray processing are primarily designed for interference suppression and do not incorporate efficient hierarchical positioning processes for near-field discrimination and coarse distance measurement scenarios. This makes it impossible to quickly distinguish between near and far-field targets and perform preliminary ranging, hindering the utilization of the lightweight advantages of subarray processing. In addition, while high-resolution positioning methods for mixed near-field and far-field sources can improve positioning accuracy to some extent, they lack a rapid near-field discrimination mechanism, resulting in high computational complexity. This makes it impossible to achieve low-complexity, rapid near-field target direction finding and ranging in large-aperture arrays, failing to meet the core requirements of balancing real-time performance and high accuracy in engineering applications.

[0060] Meanwhile, in practical marine exploration applications, large-aperture arrays often face complex marine environments and diverse target distribution scenarios, with near-field and far-field targets potentially coexisting, further exacerbating the difficulty of localization. Traditional technologies lack efficient hierarchical discrimination and adaptation mechanisms. Either their use of full-field scanning results in insufficient real-time performance, failing to respond promptly to dynamic changes in targets; or their lack of rapid near-field and far-field differentiation capabilities leads to the misuse of far-field models to handle near-field targets, resulting in localization distortion. This not only affects the efficiency of the detection system and wastes resources, but more seriously, it reduces the system's detection reliability, leading to missed or incorrect detections of key targets, failing to meet the engineering application requirements of modern sonar systems for accurate detection and rapid response. In summary, existing technologies for near-field localization of large-aperture arrays have certain systemic defects in terms of real-time performance, localization accuracy, complexity control, and environmental adaptability, failing to meet the urgent needs of modern sonar systems for rapid, high-precision passive direction finding and ranging of near-field targets.

[0061] To address the problems existing in the aforementioned related technologies, this embodiment provides a method, system, electronic device, and storage medium for rapid passive direction finding and ranging of near-field targets with a large aperture array.

[0062] Combination Figure 1 As shown in the figure, the present invention provides a fast passive direction finding and ranging method for near-field targets with a large aperture array, comprising:

[0063] Obtain the target array, and based on the array's natural directivity calculation formula, obtain the theoretical main lobe width of the target array;

[0064] Specifically, in this embodiment, the theoretical main lobe width refers to the half-power point beamwidth derived from the array's natural directivity, representing the array's theoretical resolution for signals in a specific direction under the far-field plane wave assumption.

[0065] The received signal of the target array is processed by far-field beamforming to obtain a spatial spectrum, and the measured bandwidth of the target array is extracted based on the spatial spectrum.

[0066] Specifically, in this embodiment, the measured bandwidth of the target array, taking the -3dB measured bandwidth (spectral peak width) as an example, refers to the angle difference corresponding to the 3dB drop on both sides of the maximum value of the local spectral peak in the spatial spectrum. For near-field targets, due to wavefront curvature, if a far-field model is used for spatial spectrum estimation, it will result in a significant broadening of the spectral peak.

[0067] The measured bandwidth is compared with k times the theoretical main lobe width. If the measured bandwidth is less than or equal to k times the theoretical main lobe width, the target array is located in the far field, and the azimuth spectrum result is output. If the measured bandwidth of the target array is greater than k times the theoretical main lobe width, the target array is divided into two sub-arrays, the theoretical far-field beamwidth of the two sub-arrays is calculated, and the received signal of the sub-arrays is processed by far-field beamforming to obtain the actual spectral peak width.

[0068] Specifically, this embodiment utilizes the characteristic that the spectral peak of a near-field target significantly broadens under far-field beamforming. By comparing the measured bandwidth with the theoretical beamwidth (theoretical main lobe width), it can quickly and quantitatively determine whether the target is located in the near field, avoiding the huge computational burden of full-domain two-dimensional scanning in traditional methods, and achieving rapid discrimination between near and far-field targets. In this embodiment, k is a near-field decision threshold coefficient, typically greater than 1.5, used to eliminate the beam broadening effect caused by the signal-to-noise ratio, making the discrimination more accurate.

[0069] Obtain the theoretical beamwidth, compare the actual spectral peak width with the theoretical beamwidth. If the actual spectral peak width is greater than k times the theoretical beamwidth, divide the current subarray into 2 new subarrays and repeat the process until it is less than k times the theoretical beamwidth. If the actual spectral peak width is less than or equal to k times the theoretical beamwidth, obtain the near-field and far-field critical distances based on the aperture of the current subarray.

[0070] Specifically, in this embodiment, the step-by-step subarray division refers to progressively decomposing the large-aperture array into smaller subarrays. As the aperture of the subarray decreases, its corresponding near-field region also shrinks. The near-field and far-field critical distance marks the boundary where the target moves from the near field to the far field and serves as the central reference point for fine scanning. This embodiment progressively narrows the possible distance range of the target by dividing the subarray step-by-step and repeatedly comparing beamwidths. When the target is determined to be close to the far-field boundary relative to a certain subarray, it means that the relationship between the aperture of that subarray and the target distance meets the far-field condition. At this point, the approximate distance of the target can be estimated based on the aperture of that subarray, thus achieving a rough distance measurement. This provides a convergent and smaller search interval for subsequent fine scanning, avoiding blind large-scale searches and significantly reducing computational complexity. It can be understood that the current array is continuously and equally divided into two subarrays according to element numbers, with each subarray containing the same number of elements and without overlap. If the number of elements in the original array is even, the number of elements in the two subarrays is equal; if it is odd, the difference in the number of elements in the two subarrays does not exceed 1, to ensure that the apertures of the subarrays are as close as possible. The geometric centers of the two subarrays after division point in the same direction, and the element spacing distribution characteristics of the original array are maintained.

[0071] Centered on the near and far field critical distance, a near field focusing scan is performed within a preset range. The output beamwidth at different distances is compared, and the azimuth and distance values ​​corresponding to the narrowest beam are taken. Based on the azimuth and distance values, a near field focusing scan is performed to obtain the azimuth history map and distance tracking curve of the target array.

[0072] Specifically, in this embodiment, near-field focusing scanning refers to beamforming in the near-field region by constructing a near-field steering vector that considers wavefront curvature, so that the array's focus is aligned with a specific distance and azimuth, thereby achieving accurate detection of near-field targets. The narrowest beamwidth indicates the best focusing effect, corresponding to the most accurate azimuth and distance. The azimuth history diagram is used to record the target's azimuth change trajectory at different times. The range tracking curve is used to record the target's distance change trajectory at different times.

[0073] Specifically, after obtaining the approximate distance to the target through coarse measurement, this embodiment does not perform a full-area scan. Instead, it performs a fine near-field focused scan within a limited distance range centered on the critical distance. Near-field focused beamforming compensates for the wavefront bending effect of the near-field signal, ensuring the beamwidth is minimized at the correct target distance and azimuth, thus achieving high-precision azimuth and distance measurement. This two-step positioning strategy combining coarse and fine measurement significantly reduces computational complexity while maintaining positioning accuracy. Furthermore, by continuously recording and updating the target's azimuth and distance information, moving targets can be dynamically tracked, providing information on the target's motion status and enhancing the system's practicality and target tracking capabilities.

[0074] Combination Figure 2 As shown, this embodiment of the invention first derives the theoretical main lobe width based on the array's natural directivity. Simultaneously, it performs far-field beamforming on the received array signal and extracts the measured -3dB bandwidth of the spatial spectrum. By comparing the measured beamwidth with a threshold multiple of the theoretical beamwidth, it achieves rapid near-field and far-field initial discrimination. This eliminates the need for complex two-dimensional traversal across the entire domain, directly determining the target's location and avoiding the array gain attenuation and large direction-finding deviations caused by directly using far-field models to handle near-field targets. For targets identified as near-field, this invention employs a step-by-step bisection iterative discrimination strategy. By continuously performing aperture segmentation and beamwidth comparison verification on the subarrays, it gradually converges to subarrays that meet the threshold conditions. The near-field and far-field critical distances are then calculated based on the qualified subarray aperture. This hierarchical iterative discrimination method replaces the traditional two-dimensional global distance-angle joint scanning of the entire array, significantly reducing the computational dimensionality and data processing volume, lowering algorithm complexity, and improving real-time performance. A hierarchical positioning system is constructed, consisting of initial overall array assessment, iterative subarray subdivision, and critical distance calculation. This system eliminates the need for complex high-resolution parameter estimation, relying solely on beamwidth differences to distinguish near and far fields and calibrate critical distances, thus adapting to rapid near-field target differentiation in large-aperture arrays. After calculating the near and far field critical distances, a small-range near-field focusing scan is performed centered on these critical distances. The parameters corresponding to the minimum beamwidth are used as the optimal distance and target azimuth. Based on the optimal distance, full-space near-field focusing beamforming is then completed, updating the azimuth history slices and generating azimuth history maps and range tracking curves. This approach reduces the scanning range while maintaining ranging and direction-finding accuracy, accommodating the engineering application requirements of rapid processing, low computational load, and high-precision positioning and tracking in large-aperture array scenarios.

[0075] Optionally, obtaining the target array, based on the array's natural directivity calculation formula, to obtain the theoretical main lobe width of the target array, includes:

[0076] The target array is obtained, and the theoretical main lobe width of the target array is obtained based on the array's natural directivity calculation formula. ,

[0077] In the formula, θ DT The theoretical main lobe width of the target array is given by M, where M is the number of array elements and d is the element spacing. Let θ be the signal wavelength. p Let K be the incident azimuth angle of the target array, and K be a preset angle conversion constant.

[0078] Specifically, in this embodiment, the preset angle conversion constant K ranges from 50 to 51.5. This embodiment introduces a formula for calculating the main lobe width of the array's natural directivity theory, which includes a target incident azimuth correction term. This formula can accurately calculate the array's theoretical main lobe width at any angle in real time based on the actual incident azimuth of the target. This breaks through the application limitations of the traditional fixed-azimuth theoretical beamwidth formula and achieves quantitative calculation of beamwidth that is adaptable to the entire spatial domain. Using this as a unified quantitative benchmark for near-field discrimination, the near-field and far-field discrimination of the target can be quickly determined by comparing the measured spectral peak width with the threshold of the theoretical beamwidth. This effectively replaces the traditional high-computing-power full-domain two-dimensional scanning process, significantly reducing the computational complexity of the algorithm and improving the real-time performance of the system. At the same time, this theoretical beamwidth can be used throughout the entire array and the iterative discrimination process of each level of subarray. This provides a stable and unified evaluation standard for subarray hierarchical division and near-field critical distance calculation, fundamentally avoiding the problem of deterioration in direction finding accuracy caused by near-field spherical wave distortion of large-aperture arrays. This provides a reliable theoretical basis for subsequent near-field focusing scanning and high-precision passive direction finding and ranging.

[0079] Furthermore, the specific steps of the array natural directivity calculation formula include:

[0080] Obtain the target array, construct an array coordinate system with east as the x-axis and north as the y-axis, and define the target azimuth as an angle of north-east. Based on the incident azimuth of the p-th target... The target array is presumably configured so that each element receives a far-field plane wave with the same frequency, phase, and amplitude. The directivity function of the target array is determined based on the phase difference between adjacent elements. ,

[0081] In the formula, M is the number of array elements, and d is the spacing between array elements. The signal wavelength is and satisfies =c / f, where c is the speed of sound in water, f is the signal frequency, and θ p The incident azimuth angle of the target array;

[0082] Combining the theory of natural directivity of arrays, and taking the amplitude of the directivity function decreasing to a preset decibel as the criterion for determining the half-power point, the derivation is simplified by substituting the normal incident direction of the target array.

[0083] The formula for calculating the natural directivity of the array was determined. .

[0084] Specifically, this embodiment derives a universal directivity function for a uniform linear array from the array geometry model and the far-field plane wave propagation mechanism. Combined with the 3dB half-power point criterion, theoretical simplification is performed layer by layer, ultimately yielding a dual-system formula for calculating the array main lobe width in both radians and degrees. This enables accurate calculation of the theoretical beamwidth under arbitrary incident azimuths across the entire spatial domain. The entire derivation process is complete in mechanism and well-founded in theory. The obtained theoretical main lobe width possesses rigorous physical connotations and complete parameter adaptability, serving as a unified and stable quantitative evaluation benchmark for subsequent near-field classification, subarray iterative verification, and critical distance calculation. While ensuring beamwidth calculation accuracy from the source, the beamwidth comparison and discrimination mechanism replaces the traditional high-computing-power full-domain two-dimensional scanning, effectively reducing algorithm computational complexity and improving real-time system processing performance. Simultaneously, it avoids the direction-finding performance degradation problem caused by near-field wavefront distortion of large-aperture arrays, providing a solid and reliable theoretical foundation for subsequent near-field target focusing ranging and high-precision passive direction finding.

[0085] Optionally, the step of performing far-field beamforming processing on the received signal of the target array to obtain a spatial spectrum, and extracting the measured bandwidth of the target array based on the spatial spectrum, includes:

[0086] The received signal is scanned using a far-field beamforming method. Inside, obtain the peak search function. ,as follows:

[0087] ,

[0088] Where θ is the spatial observation azimuth angle, p(θ) is the spectral peak search function, a(θ) is the array manifold steering vector corresponding to the θ direction, H is the conjugate transpose operation, and R is the data covariance matrix of the received signal;

[0089] Calculate the spatial spectral power at each angle based on the peak search function and plot the spatial spectrum.

[0090] Based on the spatial spectrum, locate the peak position of the spectrum peak and extract the angles of the left and right half-power points corresponding to a preset decibel decrease in peak power. and The measured bandwidth is obtained based on the difference between the two values, as follows:

[0091] .

[0092] In one embodiment, for a linear array, the far-field received signal can be expressed as:

[0093] ,

[0094] Among them, the guiding vector under the M element Conventional beamforming methods are used to scan the array's received signal to obtain the spatial spectrum output. Within, the spectral peak search function p( ) output by CBF )for:

[0095] ,

[0096] Among them, matrix The covariance matrix of the data, i.e. .matrix The guiding vector of the array can be represented as:

[0097] ,

[0098] Combination Figure 3 As shown, the natural directivity of the far-field CBF array is given when the array has 10 elements and a half-wavelength array configuration. Based on... Figure 2 Measuring the spectral peak width of the target: Locate the position of the maximum value of the local spectral peak and record its corresponding angle. As a coarse measurement of the target azimuth; the angles corresponding to a 3dB drop to the left and right of the peak value are taken as the left and right half-power points, respectively denoted as... and The width of the main lobe is .

[0099] When the target is located near the end-fire direction, the spatial spectrum within the range of [−90°, 90°] is periodically extended to both ends, and then the angles of the left and right 3dB half-power points are selected based on the extended spectral peaks.

[0100] This embodiment constructs a linear array far-field receiving signal model, employs conventional beamforming to complete full-domain angle scanning and output spatial spectrum, and combines a standardized 3dB half-power point determination criterion to accurately extract the measured main lobe width of the target spatial spectrum. Simultaneously, addressing the issue of the target main lobe being easily truncated by the scanning interval boundary in the end-fire direction, a spatial spectrum periodic extension method is used to complete the full spectrum, achieving distortion-free measurement of the spectral peak width across the entire spatial domain. The accurate measured spectral width data obtained in this step can be directly quantitatively compared with the theoretical main lobe width, providing a reliable data benchmark for subsequent rapid classification and discrimination of the target's near and far fields. The entire processing algorithm is mature and stable, with strong adaptability to all scenarios, and can seamlessly connect to the subsequent subarray iteration, critical distance calculation, and near-field focusing and positioning processes, balancing measurement accuracy and engineering practicality, effectively supporting rapid and high-precision passive direction finding and ranging for large-aperture arrays.

[0101] Optionally, the near-field and far-field critical distances obtained based on the aperture of the current sub-array... ,

[0102] In the formula, L is the aperture of the sub-array, λ is the signal wavelength, and α is the empirical adjustment parameter for the near-field boundary. Centered on.

[0103] Specifically, parameter α is an empirical adjustment coefficient for the near-field boundary specific to underwater acoustic scenarios, with a value range of 0.02 ≤ α ≤ 0.28. Its preferred benchmark value is α = 0.25, which corresponds to the classic Rayleigh critical distance criterion commonly used in the field of underwater acoustic arrays. In actual underwater acoustic array detection scenarios, the coefficient α can be flexibly adjusted within the above range according to the array size, operating frequency, water propagation environment, and direction finding and ranging accuracy requirements to achieve adaptive division of the near-field boundary, thereby balancing algorithm computational efficiency and overall target positioning accuracy.

[0104] Optionally, the step of performing near-field focusing scanning within a preset range, centered on the near-field and far-field critical distance, comparing the output beamwidth at different distances, and taking the azimuth and distance values ​​corresponding to the narrowest beam, includes:

[0105] Centered on the near-far field critical distance, with the lower boundary taken as 0.25 times the near-far field critical distance and the upper boundary taken as 4 times the near-far field critical distance, a preset range r∈[ , ], where L is the aperture of the subarray and λ is the signal wavelength;

[0106] Near-field focusing scanning is performed within the preset range with a preset scanning step size. The output beamwidth at different distances is compared, and the azimuth and distance values ​​corresponding to the narrowest beam are taken.

[0107] Specifically, unlike the spectral peak search function for far-field targets, the near-field target spectral peak search function needs to consider the impact of target distance on beamforming output power. Construct a peak search function for the near-field CBF output within the range:

[0108] ,

[0109] The guidance vector of the p-th target can be expressed as:

[0110] ,

[0111] in, , , Let M represent the distance from the p-th target to the first array element, where M is the number of array elements. Ranging errors can cause multiple peaks in the azimuth spectrum estimation near the target's azimuth. Therefore, the main lobe angles may be equal at different distances. If the main lobe angles are equal at different distances, the azimuth corresponding to the peak value of the highest power point in the azimuth spectrum is taken as the target's reference azimuth, and the corresponding power is expressed as... Compare the degree of power decrease under a grid spacing of 1° on the left and right.

[0112] ,

[0113] The greater the power decrease, the higher the angular resolution of the azimuth spectrum result (i.e., the smaller the ranging error). For cases with a low power decrease, a small value is added to the main lobe angle, with the value being 1 / 10 of the angle search step size. Finally, the azimuth and distance corresponding to the narrowest point of the main lobe angle are taken as the azimuth and distance of the target at the current moment.

[0114] In summary, this embodiment centers on the near-field and far-field critical distances obtained through hierarchical iterative solutions, and uses the subarray aperture and signal wavelength theory to define a refined range scanning interval. This effectively overcomes the high computational cost of traditional near-field positioning's full-domain two-dimensional full-space scanning, significantly reducing invalid calculations and improving the algorithm's real-time processing efficiency. Simultaneously, it constructs a dedicated steering vector and near-field CBF spectral peak search model adapted to the propagation characteristics of near-field spherical waves, fully incorporating range-related phase compensation terms to accurately adapt to the near-field wavefront distortion characteristics of large-aperture arrays. Furthermore, it establishes a multi-dimensional optimization criterion based on the narrowest main lobe width, combined with the spectral peak power and the degree of power reduction in adjacent grids, and simultaneously employs an angle error compensation mechanism to effectively suppress multi-peak pseudo-peak interference, quantify ranging errors, and achieve high-precision joint calculation of target azimuth and range parameters. The scanning boundary in this step has a rigorous theoretical basis and broad scene adaptability, perfectly connecting the entire hierarchical positioning process before and after, providing accurate and reliable initial parameters for subsequent full-space near-field focusing and target trajectory tracking, while balancing the speed and high precision requirements of near-field detection with large-aperture arrays.

[0115] Optionally, the step of performing a near-field focusing scan based on the azimuth and the distance value to obtain the azimuth history map and range tracking curve of the target array includes:

[0116] Based on the azimuth and the distance value, a near-field focusing scan is performed to obtain a full-angle azimuth spectrum. The current time slice in the azimuth history map is updated based on the azimuth spectrum to obtain the azimuth history map and distance tracking curve of the target array.

[0117] Specifically, based on the precise target azimuth and optimal distance parameters obtained from previous steps, a directional near-field focusing scan is performed to acquire a high-quality azimuth spectrum across all angles. The azimuth history map slices are updated hourly to form a continuous and complete target azimuth history. Simultaneously, distance data at each moment is recorded to generate a continuous distance tracking curve, achieving an upgrade from single-point static positioning to full-time dynamic trajectory tracking. This completes the entire technical loop of near-field target orientation finding, ranging, and continuous trajectory monitoring. Unlike traditional techniques that require a full-range, two-dimensional scan of the entire area at every moment, this step only requires a single full-angle focusing scan based on the locked optimal target distance to update the azimuth spectrum at the current moment. This eliminates the need for repeated full-area traversal searches, significantly reducing the amount of repetitive computation at each moment. While maintaining tracking accuracy, it significantly reduces algorithm computational overhead, perfectly adapting to the engineering requirements of real-time continuous tracking of dynamic targets in marine scenarios. The azimuth history map and distance tracking curve generated in this embodiment can intuitively present the dynamic changes of target azimuth and distance over time, clearly visually displaying the target's trajectory, facilitating subsequent data analysis, hazard identification, and system status backtracking. The output format aligns with the actual engineering monitoring and equipment maintenance needs of sonar systems. Based on the optimal ranging results from the previous stage, targeted near-field spherical wave focusing compensation is completed. The azimuth spectrum updated at each moment undergoes near-field wavefront distortion correction, effectively avoiding the direction finding deviation, spectral peak distortion, and beam broadening problems caused by the far-field model, ensuring the accuracy and stability of trajectory data throughout the entire time period, and avoiding problems such as target azimuth jumps and distance calculation distortions during tracking. As the final concluding step of the entire method, it inherits all the previous processes of near-field and far-field discrimination, subarray iterative convergence, critical distance solution, and fine ranging parameter calculation, inheriting all the advantages of lightweight discrimination and high-precision parameter calculation from the previous stage, realizing a complete process from initial judgment, coarse measurement, fine measurement to dynamic continuous tracking, and a logically complete closed loop for the entire hierarchical positioning method. Meanwhile, it is understandable that when there are multiple targets, the process involves traversing each target and repeating the entire process described above to obtain the orientation history and distance curve for each target.

[0118] In one embodiment, the array is a 256-element, equally spaced half-wavelength uniform linear array with an element spacing of 1.2 m and a sound speed in water of 1500 m / s. Combined with... Figure 4 As shown, the comparison results of the azimuth spectrum obtained by focused scanning of a 1km near-field target at different distances are presented. The accuracy of the near-field target range estimation directly affects the azimuth estimation effect: when the range estimation error is large, the spatial spectrum will show a multi-peak phenomenon, making it difficult to determine the target's azimuth. Figure 4 It is evident that the smaller the distance estimation error, the narrower the spatial spectral peak.

[0119] Assume that at the initial moment, a target is incident on the linear array. This near-field moving target is located at a distance of 1000m in the -60° direction, with a signal-to-noise ratio of 10dB, and is moving away from the array in a north-northeast direction. Spatial spectrum estimation is performed at each time point, and the results are as follows. Figure 5 As shown. Taking the initial moment as an example, when using the far-field model for spatial spectrum estimation, the target spectrum in the -60° direction diverges. According to the near-field discrimination criterion in the above embodiment, the target can be determined to be in the near field.

[0120] For near-field targets, the entire array is first divided into two subarrays. The measured main lobe width and theoretical beam width of each subarray are calculated sequentially, and the ratio of these two values ​​is used to determine whether to continue dividing the array into subarrays. The decision-making process is as follows: Figure 6 As shown. Figure 6 The azimuth and distance range marked by the Chinese border serves as the range for near-field focusing fine scanning, such as... Figure 7 As shown. By Figure 7 It can be inferred that the near-field target is approximately located at (-60°, 1km). Then, proceed sequentially... Figure 5 The above processing is performed on the azimuth curve at each time step to obtain the azimuth spectrum history and azimuth and range information of the near-field target. The range corresponding to the narrowest beam is selected, and an azimuth scan with near-field focusing is performed at this range to obtain the azimuth curve from −90° to 90°. This curve replaces the far-field scan result, as shown below. Figure 8 As shown.

[0121] Depend on Figure 8 As can be seen from the azimuth timeline, compared to Figure 5 The method of this invention uses a far-field model for spatial spectrum estimation, resulting in higher angle estimation accuracy and angle resolution. Simultaneously, the target's azimuth and distance at each moment are recorded to obtain a distance tracking history curve, as shown below. Figure 9 As shown.

[0122] This invention also provides a fast passive direction finding and ranging system for near-field targets with a large aperture array, comprising:

[0123] The data acquisition unit is used to acquire the target array and obtain the theoretical main lobe width of the target array based on the array's natural directivity calculation formula.

[0124] The data extraction unit is used to perform far-field beamforming processing on the received signal of the target array to obtain a spatial spectrum, and extract the measured bandwidth of the target array based on the spatial spectrum;

[0125] The data analysis unit is used to compare the measured bandwidth with k times the theoretical main lobe width. If the measured bandwidth is less than or equal to k times the theoretical main lobe width, the target array is located in the far field, and the azimuth spectrum result is output. If the measured bandwidth of the target array is greater than k times the theoretical main lobe width, the target array is divided into two sub-arrays, the theoretical far-field beamwidth of the two sub-arrays is calculated, and the received signal of the sub-arrays is processed by far-field beamforming to obtain the actual spectral peak width.

[0126] The data analysis unit is also used to obtain the theoretical beamwidth, compare the actual spectral peak width with the theoretical beamwidth, and if the actual spectral peak width is greater than k times the theoretical beamwidth, then the current subarray is divided into 2 new subarrays, and the process is repeated until it is less than k times the theoretical beamwidth; if the actual spectral peak width is less than or equal to k times the theoretical beamwidth, the near-field and far-field critical distances are obtained based on the aperture of the current subarray.

[0127] The data processing unit is used to perform near-field focusing scans within a preset range with the near-field and far-field critical distances as the center, compare the output beamwidths at different distances, take the azimuth and distance values ​​corresponding to the narrowest beam, and perform a near-field focusing scan based on the azimuth and distance values ​​to obtain the azimuth history map and distance tracking curve of the target array.

[0128] The large aperture array near-field target rapid passive direction finding and ranging system of the present invention has the same advantages over the prior art as the above-mentioned large aperture array near-field target rapid passive direction finding and ranging method over the prior art, and will not be repeated here.

[0129] This invention also provides an electronic device, including: a processor and a memory, wherein the memory is used to store computer programs;

[0130] When the computer program is loaded by the processor, it causes the processor to execute the fast passive direction finding and ranging method for near-field targets with a large aperture array as described above.

[0131] The electronic device of the present invention has the same advantages over the prior art as the aforementioned fast passive direction finding and ranging method for near-field targets with large aperture arrays, and will not be repeated here.

[0132] This invention also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the fast passive orientation and ranging method for near-field targets with a large aperture array as described above.

[0133] The computer-readable storage medium of the present invention has the same advantages over the prior art as the aforementioned fast passive direction finding and ranging method for near-field targets with large aperture arrays, and will not be repeated here.

[0134] While the present invention has been disclosed above, its scope of protection is not limited thereto. Those skilled in the art can make various changes and modifications without departing from the spirit and scope of the present invention, and all such changes and modifications will fall within the scope of protection of the present invention.

Claims

1. A method for rapid passive direction finding and ranging of near-field targets using a large aperture array, characterized in that, The method includes: Obtain the target array, and based on the array's natural directivity calculation formula, obtain the theoretical main lobe width of the target array; The received signal of the target array is processed by far-field beamforming to obtain a spatial spectrum, and the measured bandwidth of the target array is extracted based on the spatial spectrum. The measured bandwidth is compared with k times the theoretical main lobe width. If the measured bandwidth is less than or equal to k times the theoretical main lobe width, the target array is located in the far field, and the azimuth spectrum result is output. If the measured bandwidth of the target array is greater than k times the theoretical main lobe width, the target array is divided into two sub-arrays, the theoretical far-field beamwidth of the two sub-arrays is calculated, and the received signal of the sub-arrays is processed by far-field beamforming to obtain the actual spectral peak width. Obtain the theoretical beamwidth, compare the actual spectral peak width with the theoretical beamwidth. If the actual spectral peak width is greater than k times the theoretical beamwidth, divide the current subarray into 2 new subarrays and repeat the process until it is less than k times the theoretical beamwidth. If the actual spectral peak width is less than or equal to k times the theoretical beamwidth, obtain the near-field and far-field critical distances based on the aperture of the current subarray. Centered on the near and far field critical distance, a near field focusing scan is performed within a preset range. The output beamwidth at different distances is compared, and the azimuth and distance values ​​corresponding to the narrowest beam are taken. Based on the azimuth and distance values, a near field focusing scan is performed to obtain the azimuth history map and distance tracking curve of the target array.

2. The method for rapid passive direction finding and ranging of near-field targets with a large aperture array according to claim 1, characterized in that, The acquisition of the target array, based on the array's natural directivity calculation formula, yields the theoretical main lobe width of the target array, including: The target array is obtained, and the theoretical main lobe width of the target array is obtained based on the array's natural directivity calculation formula. , In the formula, θ DT The theoretical main lobe width of the target array is given by M, where M is the number of array elements and d is the element spacing. Let θ be the signal wavelength. p Let K be the incident azimuth angle of the target array, and K be a preset angle conversion constant.

3. The method for rapid passive direction finding and ranging of near-field targets with a large aperture array according to claim 2, characterized in that, The formula for calculating the natural directivity of the array includes the following steps: Obtain the target array, construct an array coordinate system with east as the x-axis and north as the y-axis, and define the target azimuth as an angle of north-east. Based on the incident azimuth of the p-th target... The target array is presumably configured so that each element receives a far-field plane wave with the same frequency, phase, and amplitude. The directivity function of the target array is determined based on the phase difference between adjacent elements. , In the formula, M is the number of array elements, and d is the spacing between array elements. The signal wavelength is and satisfies =c / f, where c is the speed of sound in water, f is the signal frequency, and θ p The incident azimuth angle of the target array; Combining the theory of natural directivity of arrays, and taking the amplitude of the directivity function decreasing to a preset decibel as the criterion for determining the half-power point, the derivation is simplified by substituting the normal incident direction of the target array. The formula for calculating the natural directivity of the array was determined. .

4. The method for rapid passive direction finding and ranging of near-field targets with a large aperture array according to claim 1, characterized in that, The step of performing far-field beamforming processing on the received signal of the target array to obtain a spatial spectrum, and extracting the measured bandwidth of the target array based on the spatial spectrum, includes: The received signal is scanned using a far-field beamforming method. Inside, obtain the peak search function. ,as follows: ， Where θ is the spatial observation azimuth angle, p(θ) is the spectral peak search function, a(θ) is the array manifold steering vector corresponding to the θ direction, H is the conjugate transpose operation, and R is the data covariance matrix of the received signal; Calculate the spatial spectral power at each angle based on the peak search function and plot the spatial spectrum. Based on the spatial spectrum, locate the peak position of the spectrum peak and extract the angles of the left and right half-power points corresponding to a preset decibel decrease in peak power. and The measured bandwidth is obtained based on the difference between the two values, as follows: 。 5. The method for rapid passive direction finding and ranging of near-field targets with a large aperture array according to claim 1, characterized in that, The near and far field critical distances obtained based on the aperture of the current subarray , In the formula, L is the aperture of the sub-array, λ is the signal wavelength, and α is the empirical adjustment parameter for the near-field boundary. Centered on.

6. The method for rapid passive direction finding and ranging of near-field targets with a large aperture array according to claim 1, characterized in that, The step of performing near-field focusing scanning within a preset range, centered on the near-field and far-field critical distances, comparing the output beamwidths at different distances, and taking the azimuth and distance values ​​corresponding to the narrowest beam, includes: Centered on the near-far field critical distance, with the lower boundary taken as 0.25 times the near-far field critical distance and the upper boundary taken as 4 times the near-far field critical distance, a preset range r∈[ , ], where L is the aperture of the subarray and λ is the signal wavelength; Near-field focusing scanning is performed within the preset range with a preset scanning step size. The output beamwidth at different distances is compared, and the azimuth and distance values ​​corresponding to the narrowest beam are taken.

7. The method for rapid passive direction finding and ranging of near-field targets with a large aperture array according to claim 1, characterized in that, The step of performing a near-field focusing scan based on the azimuth and the distance value to obtain the azimuth history map and range tracking curve of the target array includes: Based on the azimuth and the distance value, a near-field focusing scan is performed to obtain a full-angle azimuth spectrum. The current time slice in the azimuth history map is updated based on the azimuth spectrum to obtain the azimuth history map and distance tracking curve of the target array.

8. A rapid passive direction finding and ranging system for near-field targets with a large aperture array, characterized in that, include: The data acquisition unit is used to acquire the target array and obtain the theoretical main lobe width of the target array based on the array's natural directivity calculation formula. The data extraction unit is used to perform far-field beamforming processing on the received signal of the target array to obtain a spatial spectrum, and extract the measured bandwidth of the target array based on the spatial spectrum; The data analysis unit is used to compare the measured bandwidth with k times the theoretical main lobe width. If the measured bandwidth is less than or equal to k times the theoretical main lobe width, the target array is located in the far field, and the azimuth spectrum result is output. If the measured bandwidth of the target array is greater than k times the theoretical main lobe width, the target array is divided into two sub-arrays, the theoretical far-field beamwidth of the two sub-arrays is calculated, and the received signal of the sub-arrays is processed by far-field beamforming to obtain the actual spectral peak width. The data analysis unit is also used to obtain the theoretical beamwidth, compare the actual spectral peak width with the theoretical beamwidth, and if the actual spectral peak width is greater than k times the theoretical beamwidth, then the current subarray is divided into 2 new subarrays, and the process is repeated until it is less than k times the theoretical beamwidth; if the actual spectral peak width is less than or equal to k times the theoretical beamwidth, the near-field and far-field critical distances are obtained based on the aperture of the current subarray. The data processing unit is used to perform near-field focusing scans within a preset range with the near-field and far-field critical distances as the center, compare the output beamwidths at different distances, take the azimuth and distance values ​​corresponding to the narrowest beam, and perform a near-field focusing scan based on the azimuth and distance values ​​to obtain the azimuth history map and distance tracking curve of the target array.

9. An electronic device, characterized in that, include: Processor and memory, the memory being used to store computer programs; When the computer program is loaded by the processor, it causes the processor to execute the fast passive orientation and ranging method for near-field targets with a large aperture array as described in any one of claims 1-7.

10. A 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 fast passive direction finding and ranging method for near-field targets with a large aperture array as described in any one of claims 1-7.

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