An adaptive SAR imaging method and system in complex background environment

Abstract

The present invention discloses an adaptive SAR imaging method and system in a complex background environment, which is used for building imaging. The method comprises: performing coarse imaging of a target building by SAR to generate an initial image of the target building, and obtaining a position vector of the target building; obtaining background environment variables of the target building; setting a spatiotemporal dynamic reflection model, and calculating the SAR signal reflection intensity according to the position vector of the target building and the background environment variables; obtaining the original noise signal intensity of the target building, and setting a background noise suppression model to suppress the original noise signal intensity and calculate the suppressed noise signal intensity; setting an adaptive target enhancement model, and performing signal enhancement on the initial image according to the signal reflection intensity and the suppressed noise signal intensity, calculating the enhanced target building signal intensity, and generating a final image of the target building according to the enhanced target building signal intensity.

Description

Technical Field

[0001] The present invention belongs to the technical field of SAR imaging, and more particularly, relates to an adaptive SAR imaging method and system in a complex background environment. Background Art

[0002] In the field of civil engineering, SAR imaging (Synthetic Aperture Radar Imaging) is widely used in structural monitoring, ground deformation monitoring, disaster assessment, etc., especially in monitoring large-scale and difficult-to-reach areas, showing unique advantages. The following are the main applications of SAR imaging in civil engineering:

[0003] Structural health monitoring of buildings and bridges:

[0004] Crack Monitoring and Deformation Detection: SAR can monitor cracks, displacement, and deformation in buildings and bridges in real time, helping to assess structural safety, especially in inaccessible high-rise buildings, older structures, or bridges in remote areas. Long-term SAR data can effectively track changes in structural health and promptly identify potential safety hazards.

[0005] Dynamic monitoring: For some structures with large dynamic loads (such as bridges, tunnels, etc.), SAR can monitor their dynamic responses caused by factors such as traffic loads and earthquakes during operation.

[0006] However, the existing technical solutions have low accuracy of SAR imaging and cannot meet the requirements for use in civil engineering fields with high precision requirements. Summary of the Invention

[0007] To solve the above technical problems, the present invention proposes an adaptive SAR imaging method for building imaging in a complex background environment, comprising:

[0008] Performing coarse imaging of the target building through SAR to generate an initial image of the target building and obtain a position vector of the target building;

[0009] Acquire background environment variables of the target building, wherein the background environment variables include: the density of other buildings in the area where the target building is located and the location of each of the other buildings;

[0010] Setting a spatiotemporal dynamic reflection model to calculate the SAR signal reflection intensity according to the position vector of the target building and the background environmental variables;

[0011] Obtaining the original noise signal strength of the target building, and setting a background noise suppression model to suppress the original noise signal strength, and calculating the suppressed noise signal strength;

[0012] An adaptive target enhancement model is set, and the initial image is signal enhanced according to the signal reflection intensity and the suppressed noise signal intensity, the enhanced target building signal intensity is calculated, and a final image of the target building is generated according to the enhanced target building signal intensity.

[0013] Furthermore, the spatiotemporal dynamic reflection model includes:

[0014]

[0015] in, is the time scale at time t The signal reflection intensity of the synthetic aperture radar of the target building at position (x, y) is given below, Ω is the time range of integration, γ1 is the third adjustment factor of the spatiotemporal dynamic reflection model, α1 is the fourth adjustment factor of the spatiotemporal dynamic reflection model, r(x, y, t) is the position vector of the target building at position (x, y) at time t, r ζ (ζ) is the position vector of the background environment variable, r ζ (ζ) is the position vector of the other buildings closest to the target building, β1 is the fifth adjustment factor of the space-time dynamic reflection model, γ2 is the sixth adjustment factor of the space-time dynamic reflection model, ζ is the background environment variable, λ1 is the first adjustment factor of the space-time dynamic reflection model, λ2 is the second adjustment factor of the space-time dynamic reflection model, ρ(x, y, t, τ) is the space-time correlation function of the synthetic aperture radar at position (x, y) at time t and time delay τ, which is used to adjust the reflection response of the synthetic aperture radar under different time and space conditions.

[0016] Furthermore, the spatiotemporal correlation function ρ(x, y, t, τ) of the synthetic aperture radar at position (x, y) at time t and time delay τ includes:

[0017] ρ(x,y,t,T)=exp(-δ1·(||r(x,y,t)-r0|| 2 +τ 2 ))

[0018] Among them, δ1 is the adjustment factor of the spatiotemporal correlation function, and r0 is the position vector of the fixed reference point.

[0019] Furthermore, the background noise suppression model includes:

[0020]

[0021] in, is the noise signal strength of the target building at position (x, y) after suppression at time t, is the original noise signal strength of the target building at position (x, y) at time t, α is the first adjustment factor of the background noise suppression model, λ is the second adjustment factor of the background noise suppression model, α2 is the third adjustment factor of the background noise suppression model, γ is the fourth adjustment factor of the background noise suppression model, and β is the fifth adjustment factor of the background noise suppression model. is the coupling function of the noise signal strength and the target building signal strength at the position (x, y) at time t, which is used to reflect the local characteristics of the noise.

[0022] Furthermore, the coupling function of the noise signal strength of the target building at position (x, y) at time t and the target building signal strength is include:

[0023]

[0024] Among them, β2 is the adjustment factor of the coupling function, r noise is the location of the noise source.

[0025] Furthermore, the adaptive target enhancement model includes:

[0026]

[0027] in, is the time scale at time t where ζ′(x, y, t) is the time-dependent factor of the target building at position (x, y) at time t, which is used to reflect the temporal variation of the target building signal strength.

[0028] The present invention also proposes an adaptive SAR imaging system in a complex background environment for building imaging, comprising:

[0029] An initial image generation module is used to perform coarse imaging of a target building through SAR, generate an initial image of the target building, and obtain a position vector of the target building;

[0030] A background environment variable acquisition module is used to acquire background environment variables of the target building, wherein the background environment variables include: the density of other buildings in the area where the target building is located and the position of each of the other buildings;

[0031] A signal reflection intensity calculation module is used to set a spatiotemporal dynamic reflection model and calculate the SAR signal reflection intensity according to the position vector of the target building and the background environmental variables;

[0032] A noise suppression module is used to obtain the original noise signal strength of the target building, set a background noise suppression model, suppress the original noise signal strength, and calculate the noise signal strength after suppression;

[0033] The target enhancement module is used to set an adaptive target enhancement model, and perform signal enhancement on the initial image according to the signal reflection intensity and the suppressed noise signal intensity, calculate the enhanced target building signal intensity, and generate a final image of the target building according to the enhanced target building signal intensity.

[0034] Furthermore, the spatiotemporal dynamic reflection model includes:

[0035]

[0036] in, is the time scale at time t The signal reflection intensity of the synthetic aperture radar of the target building at position (x, y) is given below, Ω is the time range of integration, γ1 is the third adjustment factor of the spatiotemporal dynamic reflection model, α1 is the fourth adjustment factor of the spatiotemporal dynamic reflection model, r(x, y, t) is the position vector of the target building at position (x, y) at time t, r ζ (ζ) is the position vector of the background environment variable, r ζ (ζ) is the position vector of the other buildings closest to the target building, β1 is the fifth adjustment factor of the space-time dynamic reflection model, γ2 is the sixth adjustment factor of the space-time dynamic reflection model, ζ is the background environment variable, λ1 is the first adjustment factor of the space-time dynamic reflection model, λ2 is the second adjustment factor of the space-time dynamic reflection model, ρ(x, y, t, τ) is the space-time correlation function of the synthetic aperture radar at position (x, y) at time t and time delay τ, which is used to adjust the reflection response of the synthetic aperture radar under different time and space conditions.

[0037] Furthermore, the spatiotemporal correlation function ρ(x, y, t, τ) of the synthetic aperture radar at position (x, y) at time t and time delay τ includes:

[0038] ρ(x,y,t,T)=exp(-δ1·(||r(x,y,t)-r0|| 2 +τ 2 ))

[0039] Among them, δ1 is the adjustment factor of the spatiotemporal correlation function, and r0 is the position vector of the fixed reference point.

[0040] Furthermore, the background noise suppression model includes:

[0041]

[0042] in, is the noise signal strength of the target building at position (x, y) after suppression at time t, is the original noise signal strength of the target building at position (x, y) at time t, α is the first adjustment factor of the background noise suppression model, λ is the second adjustment factor of the background noise suppression model, θ2 is the third adjustment factor of the background noise suppression model, γ is the fourth adjustment factor of the background noise suppression model, and β is the fifth adjustment factor of the background noise suppression model. is the coupling function of the noise signal strength and the target building signal strength at the position (x, y) at time t, which is used to reflect the local characteristics of the noise.

[0043] In general, the above technical solutions conceived by the present invention have the following beneficial effects compared with the prior art:

[0044] Through the above technical solution, the present invention can accurately image buildings through SAR and suppress the influence of noise on imaging accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a flow chart of the method of embodiment 1 of the present invention;

[0046] Figure 2 This is a system structure diagram of Example 2 of the present invention. DETAILED DESCRIPTION

[0047] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0048] The method provided by the present invention can be implemented in the following terminal environment, wherein the terminal may include one or more of the following components: a processor, a storage medium, and a display screen. The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the method described in the following embodiments.

[0049] A processor can include one or more processing cores. It connects various components within the terminal using various interfaces and circuits. It executes instructions, programs, code sets, or instruction sets stored in storage media, and accesses data stored in storage media to perform various terminal functions and process data.

[0050] The storage medium may include a random access memory (RAM) or a read-only memory (ROM). The storage medium may be used to store instructions, programs, codes, code sets, or instructions.

[0051] The display is used to show the user interface of each application.

[0052] In addition, those skilled in the art will appreciate that the structure of the terminal described above does not limit the terminal. The terminal may include more or fewer components, or a combination of certain components, or a different arrangement of components. For example, the terminal may also include a radio frequency circuit, an input unit, a sensor, an audio circuit, a power supply, and other components, which will not be described in detail here.

[0053] Example 1

[0054] like Figure 1 As shown, an embodiment of the present invention provides an adaptive SAR imaging method in a complex background environment for building imaging, comprising:

[0055] Step 101: Performing coarse imaging of a target building through SAR to generate an initial image of the target building and obtain a position vector of the target building;

[0056] Step 102: Obtain background environment variables of the target building, wherein the background environment variables include: the density of other buildings in the area where the target building is located and the location of each of the other buildings;

[0057] Step 103: Setting a spatiotemporal dynamic reflection model to calculate the SAR signal reflection intensity based on the position vector of the target building and the background environmental variables;

[0058] Specifically, the spatiotemporal dynamic reflection model includes:

[0059]

[0060] in, is the time scale at time t The signal reflection intensity of the synthetic aperture radar of the target building at position (x, y) is given below. Ω is the time range of integration, γ1 is the third adjustment factor of the spatiotemporal dynamic reflection model, θ1 is the fourth adjustment factor of the spatiotemporal dynamic reflection model, r(x, y, t) is the position vector of the target building at position (x, y) at time t, r ζ (ζ) is the position vector of the background environment variable, r ζ(ζ) is the position vector of the other buildings closest to the target building, β1 is the fifth adjustment factor of the space-time dynamic reflection model, γ2 is the sixth adjustment factor of the space-time dynamic reflection model, ζ is the background environment variable, λ1 is the first adjustment factor of the space-time dynamic reflection model, λ2 is the second adjustment factor of the space-time dynamic reflection model, ρ(x, y, t, τ) is the space-time correlation function of the synthetic aperture radar at position (x, y) at time t and time delay τ, which is used to adjust the reflection response of the synthetic aperture radar under different time and space conditions.

[0061] About scale An example of this could be the resolution scale, specifically:

[0062] In SAR imaging, resolution is a key factor affecting reflection intensity. At different resolutions, the imaging system's observation range and level of detail of the target vary. The scale parameter SSS can be adjusted based on the resolution. For example:

[0063] In high-resolution mode, SAR can discern smaller details (such as the outline of a single building), so the scale parameter A smaller value can be used.

[0064] In low-resolution mode, the system focuses on a larger target or background area, and the scale parameter SSS can take a larger value.

[0065] For example:

[0066] High-resolution mode (e.g., 10cm resolution), scale parameter A possible value is 0.1 (reflecting the detail response of high-resolution imaging).

[0067] Low resolution mode (e.g., 1m resolution), scale parameter A possible value is 1.0 (reflecting the larger area response of low-resolution imaging).

[0068] Specifically, the spatiotemporal correlation function ρ(x, y, t, τ) of the synthetic aperture radar at position (x, y) at time t and time delay τ includes:

[0069] ρ(x,y,t,τ)=exp(-δ1·(||r(x,y,t)-r0|| 2 +τ 2 ))

[0070] Among them, δ1 is the adjustment factor of the spatiotemporal correlation function, and r0 is the position vector of the fixed reference point.

[0071] Step 104: obtaining the original noise signal strength of the target building, setting a background noise suppression model, suppressing the original noise signal strength, and calculating the suppressed noise signal strength;

[0072] Specifically, the background noise suppression model includes:

[0073]

[0074] in, is the noise signal strength of the target building at position (x, y) after suppression at time t, is the original noise signal strength of the target building at position (x, y) at time t, α is the first adjustment factor of the background noise suppression model, λ is the second adjustment factor of the background noise suppression model, α2 is the third adjustment factor of the background noise suppression model, γ is the fourth adjustment factor of the background noise suppression model, and β is the fifth adjustment factor of the background noise suppression model. is the coupling function of the noise signal strength and the target building signal strength at the position (x, y) at time t, which is used to reflect the local characteristics of the noise.

[0075] Specifically, the coupling function of the noise signal strength of the target building at position (x, y) at time t and the target building signal strength is include:

[0076]

[0077] Among them, β2 is the adjustment factor of the coupling function, r noise is the location of the noise source, which is a building, road or other interference source in the area where the target building is located.

[0078] Step 105: Set an adaptive target enhancement model, perform signal enhancement on the initial image based on the signal reflection intensity and the suppressed noise signal intensity, calculate the enhanced target building signal intensity, and generate a final image of the target building based on the enhanced target building signal intensity.

[0079] Specifically, the adaptive target enhancement model includes:

[0080]

[0081] in, is the time scale at time t where ζ′(x, y, t) is the time-dependent factor of the target building at position (x, y) at time t, which is used to reflect the temporal variation of the target building signal strength.

[0082] Example 2

[0083] like Figure 2 As shown, an embodiment of the present invention further provides an adaptive SAR imaging system in a complex background environment, which is used for building imaging, including:

[0084] An initial image generation module is used to perform coarse imaging of a target building through SAR, generate an initial image of the target building, and obtain a position vector of the target building;

[0085] A background environment variable acquisition module is used to acquire background environment variables of the target building, wherein the background environment variables include: the density of other buildings in the area where the target building is located and the position of each of the other buildings;

[0086] A signal reflection intensity calculation module is used to set a spatiotemporal dynamic reflection model and calculate the SAR signal reflection intensity according to the position vector of the target building and the background environmental variables;

[0087] Specifically, the spatiotemporal dynamic reflection model includes:

[0088]

[0089] in, is the time scale at time t The signal reflection intensity of the synthetic aperture radar of the target building at position (x, y) is given below. Ω is the time range of integration, γ1 is the third adjustment factor of the spatiotemporal dynamic reflection model, θ1 is the fourth adjustment factor of the spatiotemporal dynamic reflection model, r(x, y, t) is the position vector of the target building at position (x, y) at time t, r ζ (ζ) is the position vector of the background environment variable, r ζ (ζ) is the position vector of the other buildings closest to the target building, β1 is the fifth adjustment factor of the space-time dynamic reflection model, γ2 is the sixth adjustment factor of the space-time dynamic reflection model, ζ is the background environment variable, λ1 is the first adjustment factor of the space-time dynamic reflection model, λ2 is the second adjustment factor of the space-time dynamic reflection model, ρ(x, y, t, τ) is the space-time correlation function of the synthetic aperture radar at position (x, y) at time t and time delay τ, which is used to adjust the reflection response of the synthetic aperture radar under different time and space conditions.

[0090] Specifically, the spatiotemporal correlation function ρ(x, y, t, τ) of the synthetic aperture radar at position (x, y) at time t and time delay τ includes:

[0091] ρ(x,y,t,τ)=exp(-δ1·(||r(x,y,t)-r0|| 2 +τ 2 ))

[0092] Among them, δ1 is the adjustment factor of the spatiotemporal correlation function, and r0 is the position vector of the fixed reference point.

[0093] A noise suppression module is used to obtain the original noise signal strength of the target building, set a background noise suppression model, suppress the original noise signal strength, and calculate the noise signal strength after suppression;

[0094] Specifically, the background noise suppression model includes:

[0095]

[0096] in, is the noise signal strength of the target building at position (x, y) after suppression at time t, is the original noise signal strength of the target building at position (x, y) at time t, α is the first adjustment factor of the background noise suppression model, λ is the second adjustment factor of the background noise suppression model, θ2 is the third adjustment factor of the background noise suppression model, γ is the fourth adjustment factor of the background noise suppression model, and β is the fifth adjustment factor of the background noise suppression model. is the coupling function of the noise signal strength and the target building signal strength at the position (x, y) at time t, which is used to reflect the local characteristics of the noise.

[0097] Specifically, the coupling function of the noise signal strength of the target building at position (x, y) at time t and the target building signal strength is include:

[0098]

[0099] Among them, β2 is the adjustment factor of the coupling function, r noise is the location of the noise source.

[0100] The target enhancement module is used to set an adaptive target enhancement model, and perform signal enhancement on the initial image according to the signal reflection intensity and the suppressed noise signal intensity, calculate the enhanced target building signal intensity, and generate a final image of the target building according to the enhanced target building signal intensity.

[0101] Specifically, the adaptive target enhancement model includes:

[0102]

[0103] in, is the time scale at time t where ζ′(x, y, t) is the time-dependent factor of the target building at position (x, y) at time t, which is used to reflect the temporal variation of the target building signal strength.

[0104] Example 3

[0105] An embodiment of the present invention further provides a storage medium storing a plurality of instructions, wherein the instructions are used to implement the adaptive SAR imaging method in a complex background environment.

[0106] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a computer terminal group in a computer network, or in any mobile terminal in a mobile terminal group.

[0107] Optionally, in this embodiment, the storage medium is configured to store program codes for executing the following steps: Step 101, performing coarse imaging of a target building by SAR to generate an initial image of the target building, and obtaining a position vector of the target building;

[0108] Step 102: Obtain background environment variables of the target building, wherein the background environment variables include: the density of other buildings in the area where the target building is located and the location of each of the other buildings;

[0109] Step 103: Setting a spatiotemporal dynamic reflection model to calculate the SAR signal reflection intensity based on the position vector of the target building and the background environmental variables;

[0110] Specifically, the spatiotemporal dynamic reflection model includes:

[0111]

[0112] in, is the time scale at time t The signal reflection intensity of the synthetic aperture radar of the target building at position (x, y) is given below, Ω is the time range of integration, γ1 is the third adjustment factor of the spatiotemporal dynamic reflection model, α1 is the fourth adjustment factor of the spatiotemporal dynamic reflection model, r(x, y, t) is the position vector of the target building at position (x, y) at time t, rζ (ζ) is the position vector of the background environment variable, r ζ (ζ) is the position vector of the other buildings closest to the target building, β1 is the fifth adjustment factor of the space-time dynamic reflection model, γ2 is the sixth adjustment factor of the space-time dynamic reflection model, ζ is the background environment variable, λ1 is the first adjustment factor of the space-time dynamic reflection model, λ2 is the second adjustment factor of the space-time dynamic reflection model, ρ(x, y, t, τ) is the space-time correlation function of the synthetic aperture radar at position (x, y) at time t and time delay τ, which is used to adjust the reflection response of the synthetic aperture radar under different time and space conditions.

[0113] Specifically, the spatiotemporal correlation function ρ(x, y, t, τ) of the synthetic aperture radar at position (x, y) at time t and time delay τ includes:

[0114] ρ(x,y,t,T)=exp(-δ1·(||r(x,y,t)-r0|| 2 +τ 2 ))

[0115] Among them, δ1 is the adjustment factor of the spatiotemporal correlation function, and r0 is the position vector of the fixed reference point.

[0116] Step 104: obtaining the original noise signal strength of the target building, setting a background noise suppression model, suppressing the original noise signal strength, and calculating the suppressed noise signal strength;

[0117] Specifically, the background noise suppression model includes:

[0118]

[0119] in, is the noise signal strength of the target building at position (x, y) after suppression at time t, is the original noise signal strength of the target building at position (x, y) at time t, α is the first adjustment factor of the background noise suppression model, λ is the second adjustment factor of the background noise suppression model, θ2 is the third adjustment factor of the background noise suppression model, γ is the fourth adjustment factor of the background noise suppression model, and β is the fifth adjustment factor of the background noise suppression model. is the coupling function of the noise signal strength and the target building signal strength at the position (x, y) at time t, which is used to reflect the local characteristics of the noise.

[0120] Specifically, the coupling function of the noise signal strength of the target building at position (x, y) at time t and the target building signal strength is include:

[0121]

[0122] Among them, β2 is the adjustment factor of the coupling function, r noise is the location of the noise source.

[0123] Step 105: Set an adaptive target enhancement model, perform signal enhancement on the initial image based on the signal reflection intensity and the suppressed noise signal intensity, calculate the enhanced target building signal intensity, and generate a final image of the target building based on the enhanced target building signal intensity.

[0124] Specifically, the adaptive target enhancement model includes:

[0125]

[0126] in, is the time scale at time t where ζ′(x, y, t) is the time-dependent factor of the target building at position (x, y) at time t, which is used to reflect the temporal variation of the target building signal strength.

[0127] Example 4

[0128] An embodiment of the present invention also proposes an electronic device, including a processor and a storage medium connected to the processor, wherein the storage medium stores multiple instructions, which can be loaded and executed by the processor to enable the processor to execute the adaptive SAR imaging method in a complex background environment.

[0129] Specifically, the electronic device of this embodiment may be a computer terminal, which may include: one or more processors, and a storage medium.

[0130] The storage medium can be used to store software programs and modules, such as the program instructions / modules corresponding to the adaptive SAR imaging method for complex background environments described in an embodiment of the present invention. The processor executes the software programs and modules stored in the storage medium to perform various functional applications and data processing, thereby implementing the adaptive SAR imaging method for complex background environments described above. The storage medium can include high-speed random access memory (RAM) and non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium can further include storage media remotely located from the processor, which can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0131] The processor may call the information and application programs stored in the storage medium through the transmission system to execute the above method steps.

[0132] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0133] In the above embodiments of the present invention, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0134] In the several embodiments provided by the present invention, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the system embodiments described above are merely illustrative. For example, the division of the units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, and can be electrical or other forms.

[0135] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0136] In addition, the functional units in the various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0137] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, read-only storage medium (ROM, Read-Only Memory), random access storage medium (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk, etc. Various media that can store program codes.

[0138] Obviously, the above embodiments are merely examples for clarity of explanation and are not intended to limit the implementation methods. Those skilled in the art will readily appreciate that other variations or modifications based on the above descriptions are possible. It is not necessary and impossible to enumerate all implementation methods here. Obvious variations or modifications arising therefrom remain within the scope of protection of the present invention.

Claims

1. An adaptive SAR imaging method in a complex background environment, used for building imaging, characterized in that: include: Performing coarse imaging of the target building through SAR to generate an initial image of the target building and obtain a position vector of the target building; Acquire background environment variables of the target building, wherein the background environment variables include: the density of other buildings in the area where the target building is located and the location of each of the other buildings; Setting a spatiotemporal dynamic reflection model to calculate the SAR signal reflection intensity according to the position vector of the target building and the background environmental variables; The spatiotemporal dynamic reflection model includes: in, is the time scale at time t The signal reflection intensity of the synthetic aperture radar of the target building at position (x, y) is given below, Ω is the time range of integration, γ1 is the third adjustment factor of the spatiotemporal dynamic reflection model, α1 is the fourth adjustment factor of the spatiotemporal dynamic reflection model, r(x, y, t) is the position vector of the target building at position (x, y) at time t, r ζ (ζ) is the position vector of the other building closest to the target building, β1 is the fifth adjustment factor of the spatiotemporal dynamic reflection model, γ2 is the sixth adjustment factor of the spatiotemporal dynamic reflection model, ζ is the background environment variable, λ1 is the first adjustment factor of the spatiotemporal dynamic reflection model, λ2 is the second adjustment factor of the spatiotemporal dynamic reflection model, ρ(x, y, t, τ) is the spatiotemporal correlation function of the synthetic aperture radar at position (x, y) at time t with a time delay τ, which is used to adjust the reflection response of the synthetic aperture radar under different temporal and spatial conditions; Obtaining the original noise signal strength of the target building, and setting a background noise suppression model to suppress the original noise signal strength, and calculating the suppressed noise signal strength; Setting an adaptive target enhancement model, and performing signal enhancement on the initial image according to the signal reflection intensity and the suppressed noise signal intensity, calculating the enhanced target building signal intensity, and generating a final image of the target building according to the enhanced target building signal intensity; The adaptive target enhancement model includes: in, is the time scale at time t The enhanced signal strength of the target building at position (x, y) is shown in the figure below. δ is the first adjustment factor of the adaptive target enhancement model, φ is the second adjustment factor of the adaptive target enhancement model, ζ′(x, y, t) is the time dependency factor of the target building at position (x, y) at time t, and is used to reflect the temporal variation of the signal strength of the target building. is the noise signal strength of the target building at position (x, y) after suppression at time t.

2. The adaptive SAR imaging method in a complex background environment according to claim 1, wherein: The spatiotemporal correlation function ρ(x, y, t, τ) of a synthetic aperture radar at position (x, y) at time t and time delay τ includes: ρ(x,y,t,τ)=exp(-δ1·(||r(x,y,t)-r0|| 2 +t 2 )) Among them, δ1 is the adjustment factor of the spatiotemporal correlation function, and r0 is the position vector of the fixed reference point.

3. The adaptive SAR imaging method in a complex background environment according to claim 2, wherein: The background noise suppression model includes: in, is the noise signal strength of the target building at position (x, y) after suppression at time t, is the original noise signal strength of the target building at position (x, y) at time t, α is the first adjustment factor of the background noise suppression model, λ is the second adjustment factor of the background noise suppression model, α2 is the third adjustment factor of the background noise suppression model, γ is the fourth adjustment factor of the background noise suppression model, and β is the fifth adjustment factor of the background noise suppression model. is the coupling function of the noise signal strength and the target building signal strength at the position (x, y) at time t, which is used to reflect the local characteristics of the noise.

4. The adaptive SAR imaging method in a complex background environment according to claim 3, wherein: The coupling function of the noise signal strength and the target building signal strength at the location (x, y) at time t include: Among them, β2 is the adjustment factor of the coupling function, r noise is the location of the noise source.

5. An adaptive SAR imaging system for building imaging in a complex background environment, characterized by: include: An initial image generation module is used to perform coarse imaging of a target building through SAR, generate an initial image of the target building, and obtain a position vector of the target building; A background environment variable acquisition module is used to acquire background environment variables of the target building, wherein the background environment variables include: the density of other buildings in the area where the target building is located and the position of each of the other buildings; A signal reflection intensity calculation module is used to set a spatiotemporal dynamic reflection model and calculate the SAR signal reflection intensity according to the position vector of the target building and the background environmental variables; The spatiotemporal dynamic reflection model includes: in, is the time scale at time t The signal reflection intensity of the synthetic aperture radar of the target building at position (x, y) is given below, Ω is the time range of integration, γ1 is the third adjustment factor of the spatiotemporal dynamic reflection model, α1 is the fourth adjustment factor of the spatiotemporal dynamic reflection model, r(x, y, t) is the position vector of the target building at position (x, y) at time t, r ζ (ζ) is the position vector of the other building closest to the target building, β1 is the fifth adjustment factor of the spatiotemporal dynamic reflection model, γ2 is the sixth adjustment factor of the spatiotemporal dynamic reflection model, ζ is the background environment variable, λ1 is the first adjustment factor of the spatiotemporal dynamic reflection model, λ2 is the second adjustment factor of the spatiotemporal dynamic reflection model, ρ(x, y, t, τ) is the spatiotemporal correlation function of the synthetic aperture radar at position (x, y) at time t with a time delay τ, which is used to adjust the reflection response of the synthetic aperture radar under different temporal and spatial conditions; A noise suppression module is used to obtain the original noise signal strength of the target building, set a background noise suppression model, suppress the original noise signal strength, and calculate the noise signal strength after suppression; a target enhancement module, configured to set an adaptive target enhancement model, perform signal enhancement on the initial image based on the signal reflection intensity and the suppressed noise signal intensity, calculate the enhanced target building signal intensity, and generate a final image of the target building based on the enhanced target building signal intensity; The adaptive target enhancement model includes: in, is the time scale at time t The enhanced signal strength of the target building at position (x, y) is shown in the figure below. δ is the first adjustment factor of the adaptive target enhancement model, φ is the second adjustment factor of the adaptive target enhancement model, ζ′(x, y, t) is the time dependency factor of the target building at position (x, y) at time t, and is used to reflect the temporal variation of the signal strength of the target building. is the noise signal strength of the target building at position (x, y) after suppression at time t.

6. The adaptive SAR imaging system in a complex background environment according to claim 5, characterized in that: The spatiotemporal correlation function ρ(x, y, t, τ) of a synthetic aperture radar at position (x, y) at time t and time delay τ includes: ρ(x,y,t,τ)=exp(-δ1·(||r(x,y,t)-r0|| 2 +t 2 )) Among them, δ1 is the adjustment factor of the spatiotemporal correlation function, and r0 is the position vector of the fixed reference point.

7. The adaptive SAR imaging system in a complex background environment according to claim 6, characterized in that: The background noise suppression model includes: in, is the noise signal strength of the target building at position (x, y) after suppression at time t, is the original noise signal strength of the target building at position (x, y) at time t, α is the first adjustment factor of the background noise suppression model, λ is the second adjustment factor of the background noise suppression model, α2 is the third adjustment factor of the background noise suppression model, γ is the fourth adjustment factor of the background noise suppression model, and β is the fifth adjustment factor of the background noise suppression model. is the coupling function of the noise signal strength and the target building signal strength at the position (x, y) at time t, which is used to reflect the local characteristics of the noise.

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