Radiation source inversion positioning method and system based on diffraction calculation, electronic equipment and storage medium

Abstract

The invention discloses a radiation source single-station positioning method and system based on diffraction shadow boundary power fault detection, electronic equipment and a storage medium. The problem of positioning failure in a complex environment due to dependence on direct waves in the prior art is mainly solved. According to the implementation scheme, the method comprises the following steps: scanning and receiving a signal by using an omnidirectional antenna array, and extracting a power fault direction angle by setting a sudden drop abrupt change point in a threshold detection power curve; establishing a local coordinate system by combining known obstacle geometric information and taking an obstacle exterior angle vertex as an original point, and establishing a mathematical model according to a consistency geometric diffraction theory; a radiation source azimuth angle under a local coordinate system is calculated through the model, and then coordinate transformation is carried out on the radiation source azimuth angle to obtain an azimuth angle under global geographic coordinates. The method gets rid of dependence on a direct signal, realizes inversion positioning by using the power mutation characteristic of the diffraction shadow boundary, effectively solves the positioning problem in a complex shielding environment, is real-time and rapid, has good non-line-of-sight robustness, can independently work in a single station, and is suitable for the fields of urban anti-terrorism, spectrum supervision, emergency search and rescue and the like.

Description

Technical Field

[0001] This invention belongs to the fields of electronic reconnaissance, radio positioning and signal processing technology, and specifically relates to a radiation source inversion and positioning method and system, which can be used for single-station rapid orientation and coarse positioning of concealed signal sources in urban, mountainous and other scenarios with strong electromagnetic shielding. Background Technology

[0002] In complex electromagnetic environments, such as densely built-up urban areas or mountainous terrain, high-precision and robust localization of radiation sources remains a long-standing challenge in fields such as electronic reconnaissance, spectrum management, and public safety. Traditional localization methods based on the line-of-sight propagation assumption, such as angle of arrival (AOA) and time difference of arrival (TDOA), suffer severe performance degradation in non-line-of-sight environments because multipath, diffraction, and reflection effects make it difficult to extract direct waves, leading to the failure of geometric relationships. Existing technologies, such as models based on refined ray tracing, attempt to simulate complex paths, but they are highly dependent on the accuracy of the environmental model and incur huge computational costs; radio frequency fingerprinting matching methods require the construction and maintenance of a large static database and have poor environmental adaptability; while the generalization ability and physical interpretability of emerging deep learning methods face challenges in critical applications.

[0003] Patent document CN202010129071.7 discloses a localization method for a known scatterer location under multipath propagation conditions. It estimates the time difference between the direct and indirect waves, as well as the azimuth angles of both, by intercepting the target signal. It then calculates the distances between the scatterer and the observation station, and between the target and the observation station, estimating the target position. Finally, it determines the closed-loop solution for the distance between the target radiation source and the observation station, and the target position, obtaining the TDOA time delay difference, thereby estimating the coordinates of the undetermined node. However, because this method uses the estimated time difference between the direct and indirect waves to estimate the coordinates of the undetermined node, it is susceptible to failure in environments with strong obstruction, such as cities or mountainous areas, where the direct wave may be completely blocked or severely attenuated. This can lead to the inability to extract the direct wave information, resulting in localization failure. Meanwhile, in non-line-of-sight environments where direct waves may not exist, the first identifiable signal captured by the receiver is often a path diffracted or reflected by one or more obstacles. The TDOA time delay calculated from this path corresponds to a distance difference relative to the last reflection or diffraction point, rather than the radiation source itself. This will cause a complete error in the geometric relationship, and the positioning result will be systematically biased towards the location of the reflector, leading to positioning errors. Summary of the Invention

[0004] The purpose of this invention is to solve the problems of positioning failure, severe decrease in accuracy, or excessive cost caused by model mismatch or data dependence in the above-mentioned existing technologies under strong obstruction and non-line-of-sight environments. The invention proposes a radiation source inversion positioning method and system based on diffraction calculation to achieve accurate positioning in complex electromagnetic environments.

[0005] The core objective of this invention lies in proposing an innovative positioning mechanism that transforms obstacles into landmarks. This mechanism actively utilizes the abrupt change in received power that inevitably occurs at the boundary between the direct sunlight area and the shadow area when a signal diffracts off an obstacle such as the edge of a building. It detects and measures the azimuth angle of this power discontinuity and uses its definite physical geometric relationship with the radiation source's location to deduce the specific orientation of the radiation source. The technical solution includes:

[0006] 1. A radiation source inversion and localization method based on diffraction calculation, characterized in that it includes:

[0007] (1) Using the omnidirectional antenna mounted on a single observation station, scan and receive signals from the radiation source to be located, and accurately obtain curve data of the continuous change of the received signal power with the azimuth angle;

[0008] (2) Set a threshold to automatically identify the power drop abrupt change point on the curve caused by the diffraction shadow boundary effect, and accurately determine the azimuth angle corresponding to the abrupt change point, which is denoted as the power fault direction angle α;

[0009] (3) Obtain the known obstacle edge positions as orientation references from the pre-stored map;

[0010] (4) Establish a local relative coordinate system with the edge of the above-mentioned obstacle as the spatial reference origin. According to the consistent geometric diffraction theory, establish a deterministic mathematical model between the power fault direction angle α and the radiation source azimuth angle β at the shadow boundary: β=(α+π)mod 2π.

[0011] (5) Perform coordinate transformation on the calculated azimuth angle β of the radiation source to obtain the azimuth angle β1 of the radiation source in the global coordinate system.

[0012] Furthermore, in (4), the local relative coordinate system is established with the edge of the obstacle as the spatial reference origin. The local coordinate origin O is the outer corner vertex of the right-angle obstacle, and the positive directions of the X-axis and Y-axis are respectively taken from the origin along the two surfaces of the obstacle to the external space. In this coordinate system, the obstacle body is located in the third quadrant. This coordinate system is used to describe the relative geometric relationship between the radiation source, the observation station and the edge of the obstacle.

[0013] Furthermore, in step (4), based on the consistent geometric diffraction theory, a deterministic mathematical model is established at the shadow boundary between the power fault direction angle α and the radiation source azimuth angle β. In the local coordinate system, the positive half-axis of the X-axis is defined as the 0-degree direction, and the relationship between the radiation source azimuth angle β and α is obtained:

[0014] β = (α + π) mod 2π;

[0015] The mod operation ensures that the result of β is in the range [0, 2π).

[0016] 2. A radiation source inversion and localization system based on diffraction calculation, characterized in that it comprises:

[0017] The signal processing module is used to acquire curve data of the received signal power as a function of azimuth angle;

[0018] The mutation point detection module is used to automatically identify and extract the power tomography direction angle α by setting a threshold.

[0019] The geographic information acquisition module is used to access a pre-stored digital map database to obtain the geographic location information of the edges of known obstacles;

[0020] The geometric modeling module is used to establish a local relative coordinate system, run a deterministic mathematical model based on the consistent geometric diffraction theory, and calculate the azimuth angle β of the radiation source in the local coordinate system.

[0021] The calculation module is used to calculate the coordinate system transformation and finally obtain the azimuth angle β1 of the radiation source in the global coordinate system.

[0022] The positioning output module is used to output the final positioning result azimuth angle β1.

[0023] 3. An electronic device, characterized in that it comprises a processor, a memory, an input / output interface, and a communication interface;

[0024] The memory is used to store computer programs;

[0025] The input / output interface is used to connect the signal acquisition device, the control terminal, and the display device to realize the input of the original signal and the output of the final positioning result;

[0026] The communication interface is used to exchange data and commands with external devices through a communication protocol;

[0027] The processor is used to execute the computer program stored in the memory and implement any step in the radiation source inversion and location method based on diffraction calculation.

[0028] 4. A computer-readable storage medium, characterized in that the storage medium stores a computer program, which, when executed by a processor, implements the radiation source inversion and localization method based on diffraction calculation as described in any one of claims 1 to 5.

[0029] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0030] First, it exhibits excellent robustness in non-line-of-sight environments.

[0031] This invention eliminates the dependence on direct signals. By actively utilizing the diffraction effect of electromagnetic waves, it can perform positioning in deep shadow areas or complex urban environments where direct waves are completely blocked. Compared with traditional methods, which suffer from a sharp decline in performance or even failure due to reliance on direct waves under non-line-of-sight conditions, this invention can still achieve stable and reliable positioning without relying on direct waves, significantly improving its usability and reliability in complex electromagnetic environments.

[0032] Secondly, the deployment cost is low.

[0033] This invention requires only a single mobile observation station and coarse environmental information, without the need to deploy a large-scale sensor network or a high-precision 3D database. Compared with traditional positioning systems that require multi-station collaboration, it greatly reduces hardware deployment and maintenance costs.

[0034] Thirdly, it has strong real-time performance.

[0035] The positioning process of this invention focuses on efficient signal processing and concise geometric calculations, resulting in low computational load and fast response speed, meeting the real-time positioning requirements in highly dynamic scenarios. Compared to the complex data synchronization, backhaul, and fusion processing required by traditional multi-station systems, it avoids significant delays caused by algorithm iteration and multi-link collaboration. Attached Figure Description

[0036] Figure 1 This is a flowchart illustrating the implementation of the radiation source inversion and localization method provided in this embodiment of the invention.

[0037] Figure 2 This is a schematic diagram illustrating the establishment of a coordinate system and the visualization of the power distribution received by the observation station in the method of this invention;

[0038] Figure 3 This is a schematic diagram illustrating the visualization of the power fault received by the observation station in the method of this invention;

[0039] Figure 4 This is a schematic diagram of the geometric relationship model of the radiation source azimuth, obstacle distribution, and observation station azimuth in the method of this invention;

[0040] Figure 5 This is a schematic diagram of the radiation source inversion and positioning device provided in an embodiment of the present invention;

[0041] Figure 6 This is a schematic diagram of the structure of the electronic device provided in an embodiment of the present invention. Detailed Implementation

[0042] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0043] Example 1: Radiation Source Inversion and Location Method Based on Diffraction Calculation

[0044] Reference Figure 1 The implementation steps of this example include the following:

[0045] Step 1: Signal acquisition and power azimuth curve acquisition.

[0046] Each observation station is equipped with an omnidirectional antenna to perform a 360-degree horizontal scan within a predetermined frequency band;

[0047] The omnidirectional antenna continuously receives electromagnetic signals from the radiation source to be located, and uses spatial spectrum estimation technology to measure and record the received signal power at each azimuth angle θ in real time.

[0048] After scanning, a series of discrete azimuth angles and received power data points will be acquired. By smoothing and interpolating these data, a complete curve P(θ) is generated that continuously varies with the azimuth angle θ, as shown below. Figure 2 As shown.

[0049] This curve forms the basis for all subsequent analyses. It shows the spatial distribution characteristics of power, namely, significant intensity variations in certain orientations. The angular resolution and direction finding accuracy of the scan directly determine the richness of the curve's details.

[0050] Step 2: Identification of power abrupt change points and extraction of power fault orientation angle α.

[0051] When there is an obstruction between the observation station and the radiation source, the received signal power will decrease sharply due to diffraction along the geometric shadow boundary of the obstruction, forming a significant abrupt change point on the power curve P(θ). (See attached image) Figure 2 As shown.

[0052] from Figure 2 As can be seen, at a specific azimuth angle, such as 340°, when the distance r is 2.0m, the received power exhibits a significant jump, plummeting from -26.2dB to -33.8dB. This is a typical data manifestation of the diffraction shadow boundary effect. This phenomenon implies that the shadow boundary direction is highly deterministic and can be directly correlated to the edge of a specific obstacle, verifying the feasibility of the principle of inversion based on deterministic geometric relationships (β = α + π).

[0053] Based on this phenomenon, this step automatically detects the abrupt change point using an algorithm to overcome the problem of existing technologies relying on direct wave measurements of radiation source location. The implementation is as follows:

[0054] First, the curve P(θ) of the received signal power as a function of azimuth angle is preprocessed, and a filtering algorithm is used to smooth the data to suppress noise, providing a clean signal substrate for subsequent abrupt change detection.

[0055] Then, refer to the appendix. Figure 2Based on the analysis of typical diffraction attenuation amplitudes, a threshold is set for the value at which the curve drops to 1 / 4. Specifically, the first-order difference ΔP(θ) of the curve is calculated, and its absolute value is continuously judged in real time to determine whether it continuously exceeds the threshold, thereby initially identifying all candidate power drop regions.

[0056] Next, in order to eliminate spurious abrupt change points caused by multipath interference, the candidate region is comprehensively verified, that is, the local morphological characteristics of the power change near the point are analyzed, including the steepness of the drop and curvature characteristics, to ensure that it conforms to the sharp, unidirectional drop pattern unique to the diffraction shadow boundary; through this step, the unique principal power abrupt change point is selected from the candidate points.

[0057] Finally, the precise azimuth angle corresponding to the main abrupt change point is recorded and defined as the power fault direction angle α, which physically corresponds directly to the boundary direction between the illuminated and shadowed areas in the diffraction field.

[0058] Step 3: Obtain geographic information of the edges of known obstacles.

[0059] To achieve geometric inversion, it is necessary to determine the spatial location of the obstacle edge that causes the diffraction phenomenon. This involves:

[0060] A pre-stored digital map database containing information such as terrain and building outlines;

[0061] The station's precise positioning information obtained through GPS and the azimuth angle α obtained in step 2;

[0062] Ray tracing is performed along the α direction on the digital map to infer and retrieve the edges of significant obstacles most likely to cause this shadow boundary;

[0063] Extract the precise geographic coordinates (latitude, longitude, and elevation) of the feature points on the edge of the obstacle, and use them as spatial reference points for the next step of geometric modeling.

[0064] Step 4: Establish the local coordinate system and perform geometric calculations on the azimuth angle β of the radiation source.

[0065] 4.1) Establish a local rectangular coordinate system:

[0066] This step uses the outer corner vertex of the obstacle edge obtained in step 3 as the origin O of the local coordinate system. The directions extending from the origin O along the two surfaces of the obstacle into the external space are set as the positive directions of the X-axis and Y-axis, respectively. This ensures that the obstacle itself is naturally located in the third quadrant of the coordinate system, i.e., the region between the negative X-axis and the negative Y-axis. In this coordinate system, the observation station S is located in the fourth quadrant, and the radiation source T is located in the second quadrant. This is consistent with the attached... Figure 3 The display method is consistent with placing the main analysis area in the fourth quadrant.

[0067] 4.2) Determine the geometric relationship between the radiation source and the observation station:

[0068] According to the theory of uniform geometric diffraction, in an ideal straight-edge diffraction model, the shadow boundary is a ray originating from the origin O. The power fault direction angle α measured by observation station S, in the local coordinate system, is the opposite direction of the line of sight from radiation source T to the origin O. Therefore, the direction from the origin O to radiation source T, i.e., the azimuth angle β of the radiation source, has a fixed geometric relationship with α: they are opposite in direction, differing by 180 degrees. This relationship is consistent with the attached... Figure 4 The geometric angles marked in the figure match.

[0069] 4.3) Establish a mathematical model and perform calculations:

[0070] Based on the geometric relationship between the radiation source and the observation station, and defining the positive X-axis as the 0-degree reference in the local coordinate system, the azimuth angle β of the radiation source relative to the origin O can be calculated using the following deterministic formula:

[0071] β = (α + π) mod 2π,

[0072] The mod operation ensures that the value of the calculated result β is within the range of [0, 2π).

[0073] The azimuth angle β is calculated based on the measured α. For example, if the measured value of α is 25.9°, then the calculated value of the azimuth angle β is: β = (25.9° + 180°) mod 360° = 205.9°, which is in the range [0, 2π).

[0074] This step yields the azimuth angle β of the radiation source in a local coordinate system with the edge of the obstacle as a reference.

[0075] Step 5: Coordinate system transformation completes final positioning.

[0076] The azimuth angle β calculated in step 4 is relative to a local coordinate system, that is, with the obstacle vertex O as the origin and the building wall as the axis. In order to obtain a geographically applicable result, it must be transformed to a predefined global coordinate system.

[0077] Coordinate transformation requires two key parameters: first, the precise geographical location of the obstacle's edge vertex O in the global coordinate system; and second, the deflection angle of the positive X-axis of the local coordinate system relative to the global coordinate system, which can be directly obtained from the orientation information of building outlines in the digital map.

[0078] Using these two key parameters, the local azimuth angle β can be converted into the azimuth angle β1 in the global coordinate system through a standard two-dimensional coordinate rotation transformation, thus obtaining the final positioning angle of the radiation source.

[0079] This angle accurately indicates the true geographical direction of the radiation source from the observation station, thus enabling robust and rapid radiation source orientation relying solely on single-station measurements and basic map information, even in environments with strong obstruction and non-line-of-sight conditions.

[0080] The above implementation method transforms the disadvantages of obstacles in non-line-of-sight environments into geometric landmarks that can be used for localization through a continuous process of "signal acquisition → mutation detection → map matching → geometric inversion → coordinate transformation". As can be seen from the attached figures, data, and model, this example utilizes the following... Figure 2 Appendix Figure 3 The deterministic power mutation caused by diffraction shown and as attached Figure 4 The simple geometric relationship shown enables reliable positioning that requires no direct wave, is low-cost, and has high real-time computational performance.

[0081] Example 2: Radiation source inversion and positioning system based on diffraction calculation.

[0082] See Figure 5 This example includes: signal processing module 1, mutation point detection module 2, geographic information acquisition module 3, geometric modeling module 4, calculation module 5, and positioning output module 6. The geometric modeling module 4 includes: origin determination submodule 41, coordinate system orientation submodule 42, angle reference definition submodule 43, coordinate transformation management submodule 44, and mathematical model embedding submodule 45.

[0083] The working principle of the entire system is as follows:

[0084] The signal processing module 1 is used to acquire curve data of the received signal power changing with the azimuth angle, and transmit the curve data to the abrupt change detection module 2;

[0085] The mutation point detection module 2 is used to automatically identify and extract the power fault direction angle α by setting a threshold, and transmit the power fault direction angle α to the geometric modeling module 4;

[0086] The geographic information acquisition module 3 is used to access the pre-stored digital map database, obtain the geographic location information of the known obstacle edges, and transmit the geographic location information to the geometric modeling module 4;

[0087] The geometric modeling module 4 is used to establish a local relative coordinate system based on the power fault direction angle α from module 2 and the geographical information from module 3, and to run a deterministic mathematical model based on the consistent geometric diffraction theory. The system comprises several modules: Origin Determination Submodule 41, which accurately identifies and extracts the outer corner vertex as the origin O from geographic information and transmits O to Coordinate System Orientation Submodule 42; Coordinate System Orientation Submodule 42, based on the origin O, determines the positive directions of the X and Y axes in the local two-dimensional rectangular coordinate system from the origin along the two surfaces of the obstacle pointing towards external space, thus completing the coordinate system construction, and transmits the coordinate system information to Angle Reference Definition Submodule 43; Angle Reference Definition Submodule 43, which specifies the angle measurement reference of the local coordinate system, clearly defines the positive half-axis of the X-axis as the 0-degree azimuth reference direction and the angle value as increasing counterclockwise, and transmits the angle reference information to Coordinate Transformation Management Submodule 44; Coordinate Transformation Management Submodule 44, which establishes and manages the transformation relationship between the local coordinate system and the global geographic coordinate system, calculates and outputs the reference azimuth angle θ, and transmits θ to Mathematical Model Embedding Submodule 45; Mathematical Model Embedding Submodule 45, which encapsulates and implements the core geometric relationship β=(α+π) mod θ derived from the consistent geometric diffraction theory. 2π, thereby calculating the azimuth angle β of the radiation source in the local coordinate system, and transmitting the azimuth angle β of the radiation source in the local coordinate system and the reference azimuth angle θ to the calculation module 5;

[0088] The calculation module 5 is used to perform coordinate system transformation, and finally obtain the radiation source azimuth angle β1 in the global coordinate system, and transmit β1 to the positioning output module 6;

[0089] The positioning output module 6 is used to output the final positioning result azimuth angle β1.

[0090] The above embodiments are used to implement the corresponding methods in the aforementioned embodiment 1, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0091] It should be noted that the above functional modules can be implemented, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented in software, they can be implemented, in whole or in part, as a program instruction product. A program instruction product includes one or a set of program instructions. When the program instructions are loaded and executed on a computer, the described process or function is generated, in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The program instructions can be stored in a computer-readable and writable storage medium, or transferred from one computer's readable and writable storage medium to another.

[0092] In this embodiment, the direct coupling or communication connection between the modules can be achieved through indirect coupling or communication connection via interfaces, devices, or modules. The functional modules and sub-modules in this embodiment can dynamically reside within a single processing unit, or each module can exist physically independently, or two or more modules can dynamically reside within a single processing unit. When these dynamic components are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable and writable storage medium. This storage medium can be a memory, disk, or optical disc, etc.

[0093] Example 3, an electronic device,

[0094] Reference Figure 6 The electronic device hardware structure provided in this embodiment includes: a processor 61, a memory 62, an input / output interface 63, a communication interface 64, and a bus 65. The processor 61, memory 62, input / output interface 63, and communication interface 64 are interconnected within the device via the bus 65.

[0095] The processor 61 can be implemented using a general-purpose central processing unit (CPU), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this specification.

[0096] The memory 62 can be implemented as a read-only memory (ROM), random access memory (RAM), static storage device, dynamic storage device, etc. This memory can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 62 and called and executed by the processor 61.

[0097] The input / output interface 63 is used to connect an input / output module to realize information input and output. This input / output module can be configured as a component within the device (not shown in the figure) or connected externally to an input / output device to provide corresponding functions. Input devices include keyboards, mice, touchscreens, microphones, various sensors, etc., while output devices can include displays, speakers, vibrators, indicator lights, etc.

[0098] The communication interface 64 is used to enable communication and interaction between this device and other devices. It can communicate via wired means, such as USB or Ethernet cable, or via wireless means, such as mobile network, WIFI, or Bluetooth.

[0099] The bus 65 is used for information transmission between the various components of the device, namely the processor 61, memory 62, input / output interface 63 and communication interface 64.

[0100] It should be noted that although the above-described device only shows the processor 61, memory 62, input / output interface 63, communication interface 64, and bus 65, in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the embodiments of this specification, and not necessarily all the components shown in the figures.

[0101] This invention provides a computer-readable storage medium storing a plurality of instructions that can be loaded by a processor to execute steps in any of the radiation source inversion and localization methods based on diffraction calculations provided in this invention.

[0102] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRA), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RA), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, optical disc read-only memory (CD-ROM), digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0103] Those skilled in the art should understand that the discussion of any of the above embodiments is merely exemplary and is not intended to imply that the scope of this disclosure (including the claims) is limited to these examples; within the framework of this invention, the technical features of the above embodiments or different embodiments can also be combined, the steps can be implemented in any order, and there are many other variations of the different aspects of the invention as described above, which are not provided in detail for the sake of brevity.

[0104] Furthermore, to simplify the description and discussion, and to avoid obscuring the invention, the well-known power / ground connections to integrated circuit IC chips and other components may or may not be shown in the provided drawings. Additionally, the apparatus may be shown in block diagram form to avoid obscuring the invention, and this also takes into account the fact that the details of implementation of these block diagram apparatuses are highly dependent on the platform on which the invention will be implemented, and that such details should be entirely within the understanding of those skilled in the art. While specific details have been set forth to describe exemplary embodiments of the invention, it will be apparent to those skilled in the art that the invention may be practiced without these specific details or with variations thereof. Therefore, these descriptions should be considered illustrative rather than restrictive.

[0105] Although the present invention has been described in conjunction with specific embodiments thereof, many substitutions, modifications, and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A radiation source inversion and localization method based on diffraction calculation, characterized in that, include: (1) Using the omnidirectional antenna mounted on a single observation station, scan and receive signals from the radiation source to be located, and accurately obtain curve data of the continuous change of the received signal power with the azimuth angle; (2) Set a threshold to automatically identify the power drop abrupt change point on the curve caused by the diffraction shadow boundary effect, and accurately determine the azimuth angle corresponding to the abrupt change point, which is denoted as the power fault direction angle α; (3) Obtain the known obstacle edge positions as orientation references from the pre-stored map; (4) Establish a local relative coordinate system with the edge of the above-mentioned obstacle as the spatial reference origin. According to the consistent geometric diffraction theory, establish a deterministic mathematical model between the power fault direction angle α and the radiation source azimuth angle β at the shadow boundary: β=(α+π)mod 2π. (5) Perform coordinate transformation on the calculated azimuth angle β of the radiation source to obtain the azimuth angle β1 of the radiation source in the global coordinate system.

2. The method according to claim 1, characterized in that, The threshold setting mentioned in (2) is based on the received power curve detected by the observation station. Specifically, the threshold is set when the curve drops to 1 / 4 of its value, so as to effectively detect the angle corresponding to the power drop point.

3. The method according to claim 1, characterized in that, In (4), the local relative coordinate system is established with the edge of the obstacle as the spatial reference origin. The outer corner vertex of the right-angle obstacle is taken as the local coordinate origin O, and the directions from the origin along the two surfaces of the obstacle pointing to the external space are taken as the positive directions of the X-axis and Y-axis, respectively. In this coordinate system, the obstacle body is located in the third quadrant. This coordinate system is used to describe the relative geometric relationship between the radiation source, the observation station and the edge of the obstacle.

4. The method according to claim 1, characterized in that, In (4), based on the consistent geometric diffraction theory, a deterministic mathematical model is established at the shadow boundary between the power fault direction angle α and the radiation source azimuth angle β. In the local coordinate system, the positive half-axis of the X-axis is defined as the 0-degree direction, and the relationship between the radiation source azimuth angle β and α is obtained: β = (α + π) mod 2π; The mod operation ensures that the result of β is in the range [0, 2π).

5. The method according to claim 1, characterized in that, In step (5), the calculated azimuth angle β of the radiation source is transformed to obtain the azimuth angle β1 of the radiation source in the global coordinate system. This involves transforming the calculated azimuth angle β of the radiation source from the local relative coordinate system to the global geographic coordinate system to obtain the azimuth angle β1 of the radiation source in the global coordinate system. β1 = β + θ; Where θ is the azimuth angle of the positive X-axis direction in the local coordinate system in the global coordinate system.

6. A radiation source inversion and localization system based on diffraction calculation, characterized in that, include: The signal processing module is used to acquire curve data of the received signal power as a function of azimuth angle; The mutation point detection module is used to automatically identify and extract the power tomography direction angle α by setting a threshold. The geographic information acquisition module is used to access a pre-stored digital map database and obtain the geographic locations of the edges of known obstacles. information; The geometric modeling module is used to establish a local relative coordinate system, run a deterministic mathematical model based on the consistent geometric diffraction theory, and calculate the azimuth angle β of the radiation source in the local coordinate system. The calculation module is used to calculate the coordinate system transformation, and finally obtain the azimuth angle β of the radiation source in the global coordinate system. 1； The positioning output module is used to output the final positioning result azimuth angle β1.

7. The system according to claim 6, characterized in that, The geometric modeling module includes: The origin determination submodule is used to accurately identify and extract the outer corner vertex from the known obstacle edge position information, and establish the coordinates of the point as the spatial reference origin O of the local relative coordinate system; The coordinate system orientation submodule is used to determine the positive directions of the X and Y axes in a local two-dimensional rectangular coordinate system based on the origin O, in the direction from the origin along the two surfaces of the obstacle pointing to the external space, thereby completing the construction of the coordinate system and ensuring that the obstacle entity is fixed in the third quadrant of the coordinate system. The Angle Reference Definition submodule is used to specify the angle measurement reference of the local coordinate system, explicitly defining the positive half-axis of the X-axis as the 0-degree azimuth reference direction, and the angle value increases in the counterclockwise direction; The coordinate transformation management submodule is used to establish and manage the transformation relationship between the local coordinate system and the global geographic coordinate system, calculate and output the reference azimuth angle θ, and provide coordinate transformation support for all subsequent calculation modules. The mathematical model embedding submodule is used to encapsulate and implement the core geometric relations derived from the consistent geometric diffraction theory. Its internal execution calculation formula is β=(α+π) mod 2π.

8. An electronic device, characterized in that, include: Processor, memory, input / output interfaces, and communication interfaces; The memory is used to store computer programs; the input / output interface is used to connect signal acquisition equipment, control terminal, and display device to realize the input of raw signals. The output of the final localization result; The communication interface is used to interact with external devices for data and instructions via a communication protocol; the processor is used to execute the computer program stored in the memory and implement any one of claims 1 to 5. The radiation source inversion and localization method based on diffraction calculation described in this article.

9. The device according to claim 8, characterized in that, The communication interface, integrated into the electronic device, serves as an independent hardware communication module. It is connected to the processor and memory via the device's internal bus and is arranged in parallel with the input / output interface. Together, they form an interface component for the device to interact with the internal and external environments, providing a remote data exchange and control channel for the electronic device. It supports multiple standard network communication protocols, enabling remote reporting of positioning results, remote monitoring of system operating status, and reception and response to external control commands.

10. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the radiation source inversion and localization method based on diffraction calculation as described in any one of claims 1 to 5.

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