A single-station synthetic aperture passive location method and system based on maximum spectral sharpness criterion

Abstract

The application discloses a single-station synthetic aperture passive positioning method and system based on a maximum spectral sharpness criterion, and belongs to the fields of signal processing technology and passive positioning. The method comprises the following steps: controlling a single motion platform to continuously observe a non-cooperative radiation source and collect a time-domain baseband data sequence; constructing a virtual detection grid in a geographical space, and generating a corresponding geometric de-rotation operator for each grid node; performing point-by-point phase stripping processing on the baseband data by using the operator to obtain a residual phase sequence; mapping the residual phase sequence to a frequency domain, calculating an energy concentration norm of a spectral amplitude as a decision statistic of spatial matching; and determining the spatial coordinates of the radiation source and simultaneously inverting a transmitting-receiving frequency deviation by searching for a global maximum value point of the statistic. The application utilizes the physical characteristics that the signal frequency energy is highly concentrated under the spatial matching state, effectively avoids the defocusing problem of a traditional time-domain coherent accumulation algorithm under a frequency non-synchronous condition, and significantly improves the precision and robustness of single-station passive positioning.

Description

Technical Field

[0001] This invention belongs to the field of radio reconnaissance and passive positioning technology, specifically relating to a single-station synthetic aperture passive positioning method and system based on the maximum spectral sharpness criterion. Background Technology

[0002] In modern electromagnetic spectrum warfare, silent localization of non-cooperative radiation sources is a core capability of situational awareness. Synthetic aperture technology (SAP) uses platform motion to create a virtual large aperture, leveraging Doppler history information to achieve high azimuth angular resolution, making it the mainstream technology for single-platform passive localization. Traditional SAP localization methods, such as time-domain backprojection algorithms, are typically based on the principle of coherent accumulation of echo signals in the time domain. Their core assumption is strict frequency synchronization between the receiver's local oscillator and the transmitter's carrier wave. However, in real-world non-cooperative reconnaissance scenarios, there is often an unknown, fixed carrier frequency asynchrony deviation between the radiation source and the reconnaissance platform. This frequency deviation introduces accumulated phase error during long-term SAP integration. Under traditional coherent processing frameworks, this additional phase modulation term causes severe broadening of the main lobe of the localization function, energy diffusion, and even peak splitting, leading to a sharp deterioration in local accuracy. Existing solutions typically rely on high-dimensional frequency offset searches or complex maximum likelihood parameter estimations, which are not only computationally intensive but also exhibit poor convergence under low signal-to-noise ratio conditions and are prone to getting trapped in local optima. Therefore, there is an urgent need for a novel single-station synthetic aperture positioning method that does not require prior frequency offset information and can intrinsically resist the effects of frequency asynchrony. Summary of the Invention

[0003] To address the aforementioned technical bottlenecks, this invention proposes a single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion. This invention abandons the traditional approach of attempting complete phase compensation in the time domain, instead utilizing the physical nature of the signal's frequency domain behavior as a narrowband monotone under spatial matching conditions. It constructs a focusing evaluation system based on the energy concentration norm (fourth-order spectral moment), achieving high-precision localization under frequency offset blind conditions. To solve the technical problems, the technical solution of this invention is:

[0004] A single-station passive synthetic aperture localization method based on the maximum spectral sharpness criterion, the method comprising:

[0005] S1: Obtain the signal emitted by the non-cooperative radiation source received by the single motion platform through the antenna during the observation period, and obtain the discrete baseband signal sequence after orthogonal demodulation and analog-to-digital conversion;

[0006] S2: Construct a virtual grid within the target potential area, and use the platform motion state data to calculate the theoretical distance history of each grid node relative to the platform at each sampling time; based on the theoretical distance history, generate the geometric phase compensation factor corresponding to each grid node;

[0007] S3: Multiply the discrete baseband signal sequence by the geometric phase compensation factor of each grid node to remove the geometric modulation phase from the signal and obtain the residual phase signal sequence corresponding to each grid node.

[0008] S4: Perform time-frequency transformation on the residual phase signal sequence corresponding to each grid node to obtain the spectrum of the sequence, and calculate the metric value reflecting the concentration of spectral energy;

[0009] S5: Search for the node with the largest metric value among all grid nodes, and determine the spatial coordinates of the node as the target location of the non-cooperative radiation source.

[0010] Furthermore, in step S1, the discrete baseband signal sequence The signal model is expressed by formula (1):

[0011] (1)

[0012] in, For the signal envelope, For discrete sampling time index, The total length of the sequence. For carrier wavelength, This represents the Euclidean distance history between the platform and the real target at the sampling time. The carrier frequency asynchrony deviation between the transceiver systems The sampling interval is... Zero-mean observation noise, It is the imaginary unit.

[0013] Furthermore, in step S2, the construction process of the geometric phase compensation factor specifically includes: assuming the first... Candidate grid nodes The spatial coordinate vector is The platform in The position vector at each sampling time is ; , , Let be the three-dimensional position coordinate components of the platform at the k-th sampling time. For transpose; Let be the three-dimensional coordinate components of the m-th grid node;

[0014] Calculate the theoretical distance sequence between the grid node and the platform. This can be expressed as: Equation (2)

[0015] (2)

[0016] Based on the aforementioned theoretical distance sequence, a complex-domain geometric phase compensation factor is constructed. It can be expressed using equation (3):

[0017] (3)

[0018] It is the imaginary unit.

[0019] Furthermore, in step S3, the residual phase signal sequence The calculation formula is expressed by formula (4):

[0020] (4)

[0021] in, It represents the Hadamardi (or Hadama) stack; Represents a discrete baseband signal sequence; Represents the geometric phase compensation factor in the complex field; when the mesh nodes When the residual phase signal sequence coincides with the actual target position, The phase subject degenerates into a time index. linear functions It can be expressed using formula (5):

[0022] (5)

[0023] in, The initial phase constant is... The carrier frequency asynchrony deviation between the transceiver systems The sampling interval;

[0024] When grid nodes When deviating from the true target position, the residual phase signal sequence contains a nonlinear geometric residual phase term. It can be expressed using formula (6):

[0025] (6)

[0026] This represents the theoretical distance sequence between grid nodes and the platform. This represents the Euclidean distance history between the platform and the real target at the sampling time.

[0027] Furthermore, in step S4, the specific calculation process for calculating the metric reflecting the spectral energy concentration includes: processing the residual phase signal sequence... implement Point-based discrete Fourier transform to obtain the spectral sequence It can be expressed using formula (7):

[0028] (7)

[0029] The fourth spectral moment of the residual phase signal is calculated as the energy concentration norm. It can be expressed using formula (8):

[0030] (8)

[0031] in, The larger the value, the more concentrated the energy of the signal in the frequency domain, and the higher the corresponding time-domain phase linearity.

[0032] Furthermore, in step S5, the target location estimation specifically includes: constructing an energy concentration potential matrix. Its elements correspond to the norm of each grid node. Using a search algorithm to find the matrix The global maximum point in the value is used to determine the estimated location of the target. It can be expressed using formula (9):

[0033] (9)

[0034] At the same time, based on the spectral peak index corresponding to the maximum point The carrier frequency asynchrony deviation can be inverted using the following formula. It can be expressed using formula (10):

[0035] (10)

[0036] The sampling interval is... This represents the total length of the sequence.

[0037] A single-station synthetic aperture passive positioning system based on the maximum spectral sharpness criterion, the system comprising:

[0038] Data acquisition module: used to acquire signals emitted by non-cooperative radiation sources received by a single motion platform through an antenna during the observation period, and obtain discrete baseband signal sequences after orthogonal demodulation and analog-to-digital conversion;

[0039] Virtual network construction module: used to construct a virtual grid within the target potential area, and use platform motion state data to calculate the theoretical distance history of each grid node relative to the platform at each sampling time; based on the theoretical distance history, generate the geometric phase compensation factor corresponding to each grid node;

[0040] Phase stripping processing module: used to perform dot multiplication of the discrete baseband signal sequence with the geometric phase compensation factor of each grid node, stripping the geometric modulation phase from the signal to obtain the residual phase signal sequence corresponding to each grid node;

[0041] Focusing analysis module: used to perform time-frequency transformation on the residual phase signal sequence corresponding to each grid node, obtain the spectrum of the sequence, and calculate a metric reflecting the concentration of spectral energy;

[0042] Parameter calculation module: used to search for the node with the largest metric value among all grid nodes, and determine the spatial coordinates of the node as the target location of the non-cooperative radiation source.

[0043] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion described above.

[0044] A computer-readable storage medium storing a computer program that, when executed by a processor, implements, as described above, a single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion.

[0045] Compared with the prior art, the advantages of the present invention are as follows:

[0046] This invention discloses a single-station synthetic aperture passive positioning method and system based on the maximum spectral sharpness criterion. It utilizes the characteristic that carrier asynchrony deviation only changes the signal center frequency without altering the monotone nature of the spectrum. Regardless of the frequency deviation magnitude, the derotated signal at the true target position always maintains maximum frequency domain energy concentration, cleverly circumventing the stringent frequency synchronization requirements of traditional coherent accumulation methods. It eliminates the need for multi-dimensional carrier asynchrony deviation searches or complex parameter estimations, directly determining the position through phase characteristics. This transforms the complex parameter estimation problem into a one-dimensional focus maximization search problem, reducing computational complexity. High-precision positioning can be achieved with only a single UAV, offering flexible system deployment and low cost. Attached Figure Description

[0047] Figure 1 The present invention discloses a flowchart of a single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion;

[0048] Figure 2 A schematic diagram of the positioning geometry scene for a single-station synthetic aperture passive positioning method based on the maximum spectral sharpness criterion;

[0049] Figure 3 A comparison diagram of the frequency domain focusing characteristics of the real target node and the mismatched node in the embodiments of the present invention. Detailed Implementation

[0050] The specific implementation of the present invention is described below with reference to embodiments:

[0051] It should be noted that the structures, proportions, sizes, etc. shown in this specification are only used to complement the content disclosed in the specification for those skilled in the art to understand and read, and are not intended to limit the conditions under which the present invention can be implemented. Any modifications to the structure, changes in the proportions, or adjustments to the size, without affecting the effects and objectives that the present invention can produce, should still fall within the scope of the technical content disclosed in the present invention.

[0052] Furthermore, the terms such as "upper," "lower," "left," "right," "middle," and "one" used in this specification are merely for clarity of description and are not intended to limit the scope of the invention. Any changes or adjustments to their relative relationships, without substantially altering the technical content, should also be considered within the scope of the invention.

[0053] Example 1:

[0054] This embodiment provides a single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion. In actual non-cooperative detection, due to the asynchronous frequency of the transceiver, there is an unknown carrier asynchronous deviation in the received signal. This frequency deviation is expressed as a first-order linear growth term of the phase in the time domain.

[0055] The core principle of this invention is that the nonlinear phase term caused by the change in geometric distance in the signal can only be completely canceled when the position coordinates used for geometric phase compensation of the received signal are consistent with the actual target position. In this case, the remaining phase only contains the linear term caused by carrier asynchrony deviation. In the frequency domain, the linear phase corresponds to a single-frequency signal, whose spectral energy is highly concentrated and has high spectral sharpness; conversely, if the positions do not match, the remaining phase contains nonlinear terms and the spectral sharpness is divergent.

[0056] Specifically, it includes the following steps:

[0057] Step 1: Establish a non-cooperative discrete signal reception model: Assume the UAV platform along... The axis is cruising at a constant speed in a straight line, with a speed of The radiation source target is located at ground coordinates Due to their non-cooperative nature, there is an unknown carrier frequency asynchrony deviation between the transceiver systems. (Frequency difference). The receiver output of the first... Discrete baseband sequence of sampling points It can be expressed by formula (1):

[0058] (1)

[0059] in, For the signal envelope, For discrete sampling time index, The total length of the sequence. For carrier wavelength, This represents the Euclidean distance history between the platform and the real target at the sampling time. The sampling interval is... This represents zero-mean observation noise. The first exponential term in the formula is the nonlinear geometric phase determined by the geometric distance, and the second exponential term is determined by the frequency difference. The determined linear rotation phase.

[0060] Step 2, Spatial Meshing and Operator Construction: Construct a virtual search grid within the region of interest. For any candidate node... The theoretical distance journey between the aircraft and the platform was calculated using flight control data. It can be expressed by formula (2):

[0061] (2)

[0062] Then, based on the theoretical distance, the corresponding complex field reverse rotation operator is constructed. It can be expressed by formula (3):

[0063] (3)

[0064] Step 3, Virtual Phase Stripping: This involves stripping the received discrete signal... with operators Perform Hadamard product, phase stripping, and obtain the waveform sequence to be tested. It can be expressed by formula (4):

[0065] (4)

[0066] At this point, the phase characteristics of the compensated signal depend on the accuracy of the grid point positions. When the grid nodes match the real target (i.e., When ), the distance difference term As the signal approaches zero, the nonlinear geometric phase is precisely stripped away. At this point, the remaining signal... The phase term degenerates into a linear function, which can be expressed by formula (5):

[0067] (5)

[0068] At this time, the signal is represented by a frequency of The standard complex sine wave. When the grid nodes are mismatched, the distance difference term changes nonlinearly with time, and high-order modulation terms remain in the phase, resulting in a residual signal. It manifests as a broadband frequency modulation signal.

[0069] Step 4: Frequency Domain Focusability Measurement: To quantify the linearity of the phase trajectory, this invention uses the energy concentration norm as an evaluation index. First, for... conduct Point Fast Fourier Transform to obtain the spectral sequence It can be expressed by formula (6):

[0070] (6)

[0071] Then, the sum of squares of the normalized energy spectral density (i.e., the fourth spectral moment) is calculated as a focusing index. It can be expressed by formula (7):

[0072] (7)

[0073] in, The larger the value, the more concentrated the energy of the signal in the frequency domain, and the higher the corresponding time-domain phase linearity.

[0074] Step 5, Target Location Estimation: Traverse all grid points within the detection area, calculate the energy concentration norm corresponding to each grid point, and construct an energy concentration norm distribution map. Based on the maximum energy concentration criterion, search for the grid point with the maximum energy concentration norm as the estimated location of the radiation source target, which can be expressed by formula (8):

[0075] (8)

[0076] This node represents the estimated target location. Simultaneously, the spectral peak index corresponding to the optimal location is utilized. Inverted carrier frequency deviation It can be expressed by formula (9):

[0077] (9)

[0078] Example 2:

[0079] like Figure 1 As shown in the figure, this embodiment discloses an application scenario of a single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion. The specific implementation steps are as follows:

[0080] Assuming the drone flies at a constant speed along the Y-axis, the flight speed is... for Flight altitude: 200 meters. Radiation source carrier frequency. The frequency is 2 GHz, and the location of the radiation source is... The initial position of the drone is There is a non-cooperative residual frequency offset between the transceivers, set to 10Hz. The radiation source signal-to-noise ratio is set to 5dB, and the synthetic aperture time is [not specified]. Standardized to 10 seconds, sampling rate The frequency is 1000Hz. The geometric model is as follows: Figure 2 As shown, the error analysis of the positioning area by the single-station synthetic aperture passive positioning method based on the maximum spectral sharpness criterion is as follows: Figure 3 As shown.

[0081] Step 1: Assume the drone platform is along... The axis is cruising at a constant speed in a straight line, with a speed of The radiation source target is located at ground coordinates Due to their non-cooperative nature, there is an unknown carrier frequency asynchrony deviation between the transceiver systems. (In this example, it's 234.27Hz). The receiver output is the... Discrete baseband sequence of sampling points It can be expressed by formula (1):

[0082] (1)

[0083] in, For the signal envelope, For discrete sampling time index, The total length of the sequence. For carrier wavelength, This represents the Euclidean distance history between the platform and the real target at the sampling time. The sampling interval is... Zero-mean observation noise.

[0084] Step 2: Divide the region of interest into Cartesian coordinate grids. One virtual network (in this example, the grid range is...) The step length is 5m, that is For any candidate node The theoretical distance journey between the aircraft and the platform was calculated using flight control data. It can be expressed by formula (2):

[0085] (2)

[0086] Then, based on the theoretical distance, the corresponding complex field reverse rotation operator is constructed. It can be expressed by formula (3):

[0087] (3)

[0088] Step 3: Receive the discrete signal with operators Perform Hadamard product, phase stripping, and obtain the waveform sequence to be tested. It can be expressed by formula (4):

[0089] (4)

[0090] At this point, the phase characteristics of the compensated signal depend on the accuracy of the grid point positions. When the grid nodes match the real target (i.e., When ), the distance difference term As the signal approaches zero, the nonlinear geometric phase is precisely stripped away. At this point, the remaining signal... The phase term degenerates into a linear function, which can be expressed by formula (5):

[0091] (5)

[0092] At this time, the signal is represented by a frequency of The standard complex sine wave. When the grid nodes are mismatched, the distance difference term changes nonlinearly with time, and high-order modulation terms remain in the phase, resulting in a residual signal. It manifests as a broadband frequency modulation signal.

[0093] Step 5: Traverse all grid points within the detection area, calculate the energy concentration norm corresponding to each grid point, and construct an energy concentration norm distribution map. Based on the maximum energy concentration criterion, search for the grid point with the maximum energy concentration norm as the estimated location of the radiation source target, which can be expressed by formula (8):

[0094] (8)

[0095] in: This represents the final estimated coordinates output by the algorithm. Simultaneously, it utilizes the spectral peak index corresponding to the optimal location. Inverted carrier frequency deviation It can be expressed by formula (9):

[0096] (9)

[0097] Step Six: Solve the above optimization problem using a grid search to obtain the estimated location of the radiation source target. The positioning error was 5m. Meanwhile, by analyzing the spectral peak at the optimal location, the estimated carrier frequency deviation was 234.18Hz, with an error of only 0.09Hz. In contrast, the traditional synthetic aperture backward projection algorithm had a positioning error exceeding 500m under the same conditions.

[0098] Example 3:

[0099] This embodiment provides a single-station synthetic aperture passive localization system based on the maximum spectral sharpness criterion. The system is applied to a single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion, and includes:

[0100] Data acquisition module: used to acquire signals emitted by non-cooperative radiation sources received by a single motion platform through an antenna during the observation period, and obtain discrete baseband signal sequences after orthogonal demodulation and analog-to-digital conversion;

[0101] Virtual network construction module: used to construct a virtual grid within the target potential area, and use platform motion state data to calculate the theoretical distance history of each grid node relative to the platform at each sampling time; based on the theoretical distance history, generate the geometric phase compensation factor corresponding to each grid node;

[0102] Phase stripping processing module: used to perform dot multiplication of the discrete baseband signal sequence with the geometric phase compensation factor of each grid node, stripping the geometric modulation phase from the signal to obtain the residual phase signal sequence corresponding to each grid node;

[0103] Focusing analysis module: used to perform time-frequency transformation on the residual phase signal sequence corresponding to each grid node, obtain the spectrum of the sequence, and calculate a metric reflecting the concentration of spectral energy;

[0104] Parameter calculation module: used to search for the node with the largest metric value among all grid nodes, and determine the spatial coordinates of the node as the target location of the non-cooperative radiation source.

[0105] Example 4:

[0106] This embodiment provides a terminal device, which includes a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or corresponding function. The processor described in this embodiment can be used in the operation of a single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion, including the following steps:

[0107] S1: Obtain the signal emitted by the non-cooperative radiation source received by the single motion platform through the antenna during the observation period, and obtain the discrete baseband signal sequence after orthogonal demodulation and analog-to-digital conversion;

[0108] S2: Construct a virtual grid within the target potential area, and use the platform motion state data to calculate the theoretical distance history of each grid node relative to the platform at each sampling time; based on the theoretical distance history, generate the geometric phase compensation factor corresponding to each grid node;

[0109] S3: Multiply the discrete baseband signal sequence by the geometric phase compensation factor of each grid node to remove the geometric modulation phase from the signal and obtain the residual phase signal sequence corresponding to each grid node.

[0110] S4: Perform time-frequency transformation on the residual phase signal sequence corresponding to each grid node to obtain the spectrum of the sequence, and calculate the metric value reflecting the concentration of spectral energy;

[0111] S5: Search for the node with the largest metric value among all grid nodes, and determine the spatial coordinates of the node as the target location of the non-cooperative radiation source.

[0112] Example 5:

[0113] This embodiment provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor. These instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0114] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by the processor to perform the following steps:

[0115] S1: Obtain the signal emitted by the non-cooperative radiation source received by the single motion platform through the antenna during the observation period, and obtain the discrete baseband signal sequence after orthogonal demodulation and analog-to-digital conversion;

[0116] S2: Construct a virtual grid within the target potential area, and use the platform motion state data to calculate the theoretical distance history of each grid node relative to the platform at each sampling time; based on the theoretical distance history, generate the geometric phase compensation factor corresponding to each grid node;

[0117] S3: Multiply the discrete baseband signal sequence by the geometric phase compensation factor of each grid node to remove the geometric modulation phase from the signal and obtain the residual phase signal sequence corresponding to each grid node.

[0118] S4: Perform time-frequency transformation on the residual phase signal sequence corresponding to each grid node to obtain the spectrum of the sequence, and calculate the metric value reflecting the concentration of spectral energy;

[0119] S5: Search for the node with the largest metric value among all grid nodes, and determine the spatial coordinates of the node as the target location of the non-cooperative radiation source.

[0120] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0121] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0122] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0123] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0124] The preferred embodiments of the present invention have been described in detail above. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

[0125] Many other changes and modifications can be made without departing from the concept and scope of this invention. It should be understood that this invention is not limited to the specific embodiments, and the scope of this invention is defined by the appended claims.

Claims

1. A passive single-station synthetic aperture localization method based on the maximum spectral sharpness criterion, characterized in that, The method includes: S1: Obtain the signal emitted by the non-cooperative radiation source received by the single motion platform through the antenna during the observation period, and obtain the discrete baseband signal sequence after orthogonal demodulation and analog-to-digital conversion; S2: Construct a virtual grid within the target potential area, and use the platform motion state data to calculate the theoretical distance history of each grid node relative to the platform at each sampling time; based on the theoretical distance history, generate the geometric phase compensation factor corresponding to each grid node; S3: Multiply the discrete baseband signal sequence by the geometric phase compensation factor of each grid node to remove the geometric modulation phase from the signal and obtain the residual phase signal sequence corresponding to each grid node. S4: Perform time-frequency transformation on the residual phase signal sequence corresponding to each grid node to obtain the spectrum of the sequence, and calculate the metric value reflecting the concentration of spectral energy; S5: Search for the node with the largest metric value among all grid nodes, and determine the spatial coordinates of the node as the target location of the non-cooperative radiation source.

2. The single-station passive synthetic aperture localization method based on the maximum spectral sharpness criterion according to claim 1, characterized in that, In step S1, the discrete baseband signal sequence The signal model is expressed by formula (1): （1） in, For the signal envelope, For discrete sampling time index, The total length of the sequence. For carrier wavelength, This represents the Euclidean distance history between the platform and the real target at the sampling time. The carrier frequency asynchrony deviation between the transceiver systems The sampling interval is... Zero-mean observation noise, It is the imaginary unit.

3. The single-station passive synthetic aperture localization method based on the maximum spectral sharpness criterion according to claim 1, characterized in that, In step S2, the construction process of the geometric phase compensation factor specifically includes: assuming the first... Candidate grid nodes The spatial coordinate vector is The platform in The position vector at each sampling time is ; , , Let be the three-dimensional position coordinate components of the platform at the k-th sampling time. For transpose; Let be the three-dimensional coordinate components of the m-th grid node; Calculate the theoretical distance sequence between the grid node and the platform. This can be expressed as: Equation (2) （2） Based on the aforementioned theoretical distance sequence, a complex-domain geometric phase compensation factor is constructed. It can be expressed using equation (3): （3） It is the imaginary unit.

4. The single-station passive synthetic aperture localization method based on the maximum spectral sharpness criterion according to claim 1, characterized in that, In step S3, the residual phase signal sequence The calculation formula is expressed by formula (4): （4） in, It represents the Hadamardi (or Hadama) stack; Represents a discrete baseband signal sequence; Represents the geometric phase compensation factor in the complex field; when the mesh nodes When the residual phase signal sequence coincides with the actual target position, The phase subject degenerates into a time index. linear functions It can be expressed using formula (5): （5） in, The initial phase constant is... The carrier frequency asynchrony deviation between the transceiver systems The sampling interval; When grid nodes When deviating from the true target position, the residual phase signal sequence contains a nonlinear geometric residual phase term. It can be expressed using formula (6): （6） This represents the theoretical distance sequence between grid nodes and the platform. This represents the Euclidean distance history between the platform and the real target at the sampling time.

5. The single-station passive synthetic aperture localization method based on the maximum spectral sharpness criterion according to claim 1, characterized in that, In step S4, the specific calculation process for calculating the metric reflecting the spectral energy concentration includes: processing the residual phase signal sequence... implement Point-based discrete Fourier transform to obtain the spectral sequence It can be expressed using formula (7): （7） The fourth spectral moment of the residual phase signal is calculated as the energy concentration norm. It can be expressed using formula (8): （8） in, The larger the value, the more concentrated the energy of the signal in the frequency domain, and the higher the corresponding time-domain phase linearity.

6. The single-station passive synthetic aperture localization method based on the maximum spectral sharpness criterion according to claim 1, characterized in that, In step S5, the target location estimation specifically includes: constructing an energy concentration potential matrix. Its elements correspond to the norm of each grid node. Using a search algorithm to find the matrix The global maximum point in the value is used to determine the estimated location of the target. It can be expressed using formula (9): （9） At the same time, based on the spectral peak index corresponding to the maximum point The carrier frequency asynchrony deviation can be inverted using the following formula. It can be expressed using formula (10): （10） The sampling interval is... This represents the total length of the sequence.

7. A single-station synthetic aperture passive positioning system based on the maximum spectral sharpness criterion, characterized in that, The system includes: Data acquisition module: used to acquire signals emitted by non-cooperative radiation sources received by a single motion platform through an antenna during the observation period, and obtain discrete baseband signal sequences after orthogonal demodulation and analog-to-digital conversion; Virtual network construction module: used to construct a virtual grid within the target potential area, and use platform motion state data to calculate the theoretical distance history of each grid node relative to the platform at each sampling time; based on the theoretical distance history, generate the geometric phase compensation factor corresponding to each grid node; Phase stripping processing module: used to perform dot multiplication of the discrete baseband signal sequence with the geometric phase compensation factor of each grid node, stripping the geometric modulation phase from the signal to obtain the residual phase signal sequence corresponding to each grid node; Focusing analysis module: used to perform time-frequency transformation on the residual phase signal sequence corresponding to each grid node, obtain the spectrum of the sequence, and calculate a metric reflecting the concentration of spectral energy; Parameter calculation module: used to search for the node with the largest metric value among all grid nodes, and determine the spatial coordinates of the node as the target location of the non-cooperative radiation source.

8. A computer device, characterized in that, The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements a single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements a single-station synthetic aperture passive localization method based on the maximum spectral sharpness criterion according to any one of claims 1 to 6.

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