Self-adaptive SAR imaging method and system in complex background environment

Abstract

The invention discloses a self-adaptive SAR imaging method and system in a complex background environment, and the method is used for building imaging, and the method comprises the steps: carrying out the coarse imaging of a target building through an SAR, generating an initial image of the target building, and obtaining the position vector of the target building; obtaining a background environment variable of the target building; setting a space-time dynamic reflection model, and calculating the signal reflection intensity of the SAR according to the position vector of the target building and the background environment variable; obtaining the original noise signal intensity of the target building, setting a background noise suppression model, suppressing the original noise signal intensity, and calculating the suppressed noise signal intensity; and setting a self-adaptive target enhancement model, performing signal enhancement on the initial image according to the signal reflection intensity and the suppressed noise signal intensity, calculating the signal intensity of the enhanced target building, and generating a final image of the target building according to the signal intensity of the enhanced target building.

Description

Technical Field

[0001] The present invention belongs to the technical field of SAR imaging, and more specifically, relates to an adaptive SAR imaging method and system under 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 of buildings and bridge structures in real time, helping to assess the safety of structures, especially in inaccessible high-rise buildings, old buildings or bridges in remote areas. Through long-term series of SAR data, structural health changes can be effectively tracked and potential safety hazards can be discovered in a timely manner.

[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 accuracy of SAR imaging in existing technical solutions is low and cannot meet the requirements for use in civil engineering fields with high precision requirements. Summary of the invention

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

[0008] Performing coarse imaging of the target building through SAR, generating an initial image of the target building, and obtaining 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 position of each of the other buildings;

[0010] Setting a spatiotemporal dynamic reflection model, and calculating the signal reflection intensity of the SAR 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 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. ζ (ζ) is the position vector of the background environment variable, r ζ (ζ) is the position vector of 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 located at position (x, y) at time t with a time delay of τ, which is used to adjust the reflection response of the synthetic aperture radar under different time and space conditions.

[0016] Further, 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, β is the fifth adjustment factor of the background noise suppression model, is 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, 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 signal strength of the target building 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 scale at time t where 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.

[0028] The present invention also proposes an adaptive SAR imaging system in a complex background environment, which is used 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 signal reflection intensity of the SAR according to the position vector of the target building and the background environment variable;

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

[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 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. ζ (ζ) is the position vector of the background environment variable, r ζ (ζ) is the position vector of 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 located at position (x, y) at time t with a time delay of τ, which is used to adjust the reflection response of the synthetic aperture radar under different time and space conditions.

[0037] Further, 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, β is the fifth adjustment factor of the background noise suppression model, is 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, which is used to reflect the local characteristics of the noise.

[0043] In general, the above technical solution conceived by the present invention has 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 It is a system structure diagram of embodiment 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 in conjunction with the accompanying drawings and specific implementation methods.

[0048] The method provided by the present invention can be implemented in the following terminal environment, and 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, and the instruction is loaded and executed by the processor to implement the method described in the following embodiment.

[0049] The processor may include one or more processing cores. The processor uses various interfaces and lines to connect various parts in the entire terminal, and executes various functions of the terminal and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and calling data stored in the storage medium.

[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 screen is used to display the user interface of each application.

[0052] In addition, those skilled in the art can understand that the structure of the above terminal does not constitute a limitation on the terminal, and the terminal may include more or fewer components, or combine certain components, or arrange the components differently. For example, the terminal also includes components such as a radio frequency circuit, an input unit, a sensor, an audio circuit, and a power supply, 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, which is used for building imaging, including:

[0055] Step 101, performing coarse imaging of a target building through SAR, generating an initial image of the target building, and obtaining a position vector of the target building;

[0056] Step 102, obtaining 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;

[0057] Step 103, 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 variable;

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

[0059]

[0060] in, is the 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. ζ (ζ) is the position vector of the background environment variable, r ζ(ζ) is the position vector of 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 located at position (x, y) at time t with a time delay of 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 has different observation ranges and levels of detail for the target. The scale parameter SSS can be adjusted according to 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 Can take smaller value.

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

[0065] Example:

[0066] High resolution mode (e.g. 10cm resolution), scale parameter A possible value is 0.1 (reflecting detail response for 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, and setting a background noise suppression model to suppress 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, β is the fifth adjustment factor of the background noise suppression model, is 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, 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 signal strength of the target building is include:

[0076]

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

[0078] Step 105, 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.

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

[0080]

[0081] in, is the scale at time t where 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.

[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 signal reflection intensity of the SAR according to the position vector of the target building and the background environment variable;

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

[0088]

[0089] in, is the 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. ζ (ζ) is the position vector of the background environment variable, r ζ (ζ) is the position vector of 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 located at position (x, y) at time t with a time delay of 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, and set a background noise suppression model to suppress the original noise signal strength and calculate the suppressed noise signal strength;

[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, β is the fifth adjustment factor of the background noise suppression model, is 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, 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 signal strength of the target building 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 scale at time t where 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.

[0104] Example 3

[0105] The 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 above 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 through SAR to generate an initial image of the target building, and obtaining a position vector of the target building;

[0108] Step 102, obtaining 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;

[0109] Step 103, 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 variable;

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

[0111]

[0112] in, is the 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.ζ (ζ) is the position vector of the background environment variable, r ζ (ζ) is the position vector of 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 located at position (x, y) at time t with a time delay of 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, and setting a background noise suppression model to suppress 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, β is the fifth adjustment factor of the background noise suppression model, is 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, 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 signal strength of the target building 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, 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.

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

[0125]

[0126] in, is the scale at time t where 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.

[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 a plurality of instructions, and the instructions can be loaded and executed by the processor so that the processor can execute the adaptive SAR imaging method in a complex background environment.

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

[0130] Among them, the storage medium can be used to store software programs and modules, such as an adaptive SAR imaging method under a complex background environment in an embodiment of the present invention, and corresponding program instructions / modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the storage medium, that is, realizing the above-mentioned adaptive SAR imaging method under a complex background environment. The storage medium may include a high-speed random storage medium, and may also include a non-volatile storage medium, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include a storage medium remotely arranged relative to the processor, and these remote storage media may be connected to the terminal via a network. Examples of the above-mentioned network 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 only for description 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 emphasis. 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 only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that 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, which can be electrical or other forms.

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

[0136] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of 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, and the computer software product is stored in a storage medium, including a number of instructions for 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 and other media that can store program codes.

[0138] Obviously, the above embodiments are merely examples for the purpose of clear explanation, and are not intended to limit the implementation methods. For those skilled in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived therefrom are still within the scope of protection of the 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, generating an initial image of the target building, and obtaining 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 position of each of the other buildings; Setting a spatiotemporal dynamic reflection model, and calculating the signal reflection intensity of the SAR according to the position vector of the target building and the background environmental variables; 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; 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.

2. The adaptive SAR imaging method in a complex background environment according to claim 1, characterized in that: 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. ζ (ζ) is the position vector of the background environment variable, r ζ (ζ) is the position vector of 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 located at position (x, y) at time t with a time delay of τ, which is used to adjust the reflection response of the synthetic aperture radar under different time and space conditions.

3. The adaptive SAR imaging method in a complex background environment as claimed in claim 2, characterized in that: The spatiotemporal correlation function ρ(x, y, t, τ) of a synthetic aperture radar at position (x, y) at time t with a 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.

4. The adaptive SAR imaging method in a complex background environment as claimed in claim 3, 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, β is the fifth adjustment factor of the background noise suppression model, is 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, which is used to reflect the local characteristics of the noise.

5. The adaptive SAR imaging method in a complex background environment as claimed in claim 4, characterized in that: 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.

6. The adaptive SAR imaging method in a complex background environment as claimed in claim 5, characterized in that: The adaptive target enhancement model includes: in, is the time scale at time t where 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.

7. An adaptive SAR imaging system in a complex background environment, used for building imaging, characterized in that: 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 signal reflection intensity of the SAR according to the position vector of the target building and the background environment variable; A noise suppression module is used to obtain the original noise signal strength of the target building, and set a background noise suppression model to suppress the original noise signal strength and calculate the suppressed noise signal strength; 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.

8. The adaptive SAR imaging system in a complex background environment as claimed in claim 7, characterized in that: 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. ζ (ζ) is the position vector of the background environment variable, r ζ (ζ) is the position vector of 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 located at position (x, y) at time t with a time delay of τ, which is used to adjust the reflection response of the synthetic aperture radar under different time and space conditions.

9. The adaptive SAR imaging system in a complex background environment as claimed in claim 8, characterized in that: The spatiotemporal correlation function ρ(x, y, t, τ) of a synthetic aperture radar at position (x, y) at time t with a 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.

10. The adaptive SAR imaging system in a complex background environment as claimed in claim 9, 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, β is the fifth adjustment factor of the background noise suppression model, is 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, which is used to reflect the local characteristics of the noise.

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