Signal processing system and signal processing method

Abstract

A signal processing system 100 includes a simulated SAR image generating unit 120 for generating a simulated SAR image which is a complex image indicating a steady state suited to an imaging condition of a SAR image to be analyzed, using three-dimensional information which is data having phase information and reflection intensity information for a three-dimensional position in a steady state in which a region is reconstructed by SAR using a captured observation SAR image, and the imaging condition of the SAR image to be analyzed.

Description

[Technical field]

[0001] The present invention relates to a signal processing system, a signal processing method, and a signal processing program. [Background technology]

[0002] Patent documents 1 to 4 describe change detection techniques using SAR images. Patent document 1 describes a computer-implemented method for determining coherence between composite images having phase and amplitude components.

[0003] Furthermore, Patent Document 2 describes a method for processing SAR image data including multiple frames for each of multiple image shapes.

[0004] Also, Patent Document 3 describes a method and an apparatus for detecting at least one target in an image, the image including a set of pixels, each pixel having an assigned size.

[0005] Furthermore, Patent Document 4 describes a disaster countermeasure support method for accurately, quickly, and systematically carrying out countermeasure planning and activities during emergency response and recovery and reconstruction after a disaster occurs.

[0006] The disaster countermeasure support method described in Patent Document 4 uses a synthetic aperture radar mounted on an artificial satellite to capture images of the ground surface of a target during normal times before a disaster occurs, and acquires radar image data. The disaster countermeasure support method described in Patent Document 4 also captures images of the ground surface of a target within a period shorter than the number of days for the recurrent orbit after a disaster occurs, and strives to quickly grasp the damage situation by comparing the images with radar image data during normal times. [Prior art documents] [Patent documents]

[0007] [Patent Document 1] European Patent Application Publication No. 3540462 [Patent Document 2] GB Patent Application Publication No. 2553284 [Patent Document 3] U.S. Pat. No. 1,057,1560 [Patent Document 4] International Publication No. 2008 / 016153 Summary of the Invention [Problem to be solved by the invention]

[0008] Patent documents 1 to 4 do not disclose a technique for detecting a change from a steady state by using a complex correlation coefficient between a complex image showing a steady state according to the shooting conditions of the SAR image to be analyzed and the SAR image to be analyzed. In particular, the disaster countermeasure support method disclosed in Patent document 4 uses only the reflection intensity of the reflected wave. In other words, the techniques disclosed in Patent documents 1 to 4 cannot correctly detect a change from a steady state.

[0009] Therefore, an object of the present invention is to provide a signal processing system, a signal processing method, and a signal processing program that can correctly detect a change from a steady state. [Means for solving the problem]

[0010] The signal processing system according to the present invention is characterized in that it includes a generation means for generating a simulated SAR image, which is a complex image showing a steady state suitable for the imaging conditions of the SAR image to be analyzed, using three-dimensional information, which is data having information on reflection intensity and phase information at three-dimensional positions in a steady state reconstructed using observed SAR images captured by SAR, and the imaging conditions of the SAR image to be analyzed.

[0011] The signal processing method according to the present invention is characterized in that a computer generates a simulated SAR image, which is a complex image showing a steady state suitable for the imaging conditions of the SAR image to be analyzed, using three-dimensional information, which is data having information on reflection intensity and phase information at three-dimensional positions in a steady state reconstructed using observed SAR images captured by SAR, and the imaging conditions of the SAR image to be analyzed.

[0012] The signal processing program according to the present invention is characterized in that it causes a computer to execute a generation process for generating a simulated SAR image, which is a complex image showing a steady state suitable for the imaging conditions of the SAR image to be analyzed, using three-dimensional information, which is data having information on reflection intensity and phase information at three-dimensional positions in a steady state reconstructed using observed SAR images captured by SAR, and the imaging conditions of the SAR image to be analyzed. Effect of the Invention

[0013] According to the present invention, a change from a steady state can be correctly detected. [Brief description of the drawings]

[0014] [Figure 1] FIG. 1 is an explanatory diagram showing the relationship between the coherence value and the correlation between the reflection intensity and phase between SAR images. [Diagram 2] FIG. 1 is an explanatory diagram showing an example of a SAR satellite photographing a building. [Diagram 3] FIG. 1 is an explanatory diagram showing an example of a layover phenomenon occurring in a SAR image. [Figure 4] 1 is a block diagram showing an example of the configuration of a signal processing system according to a first embodiment of the present invention. [Diagram 5] FIG. 11 is an explanatory diagram showing an example of a method for estimating a complex reflection intensity distribution at a pixel corresponding to an azimuth-range position (x→) in SAR tomography by the three-dimensional information reconstruction unit 110. [Figure 6] 4 is a flowchart showing a signal processing operation by the signal processing system 100 of the first embodiment. [Figure 7] 5 is a flowchart showing the operation of three-dimensional information reconstruction processing by the three-dimensional information reconstruction unit 110 according to the first embodiment. [Figure 8] 5 is a flowchart showing the operation of a simulated SAR image generation process by a simulated SAR image generating unit 120 according to the first embodiment. [Figure 9] FIG. 11 is a block diagram showing an example of the configuration of a signal processing system according to a second embodiment of the present invention. [Figure 10] 10 is an explanatory diagram showing a specific example of the first motion detection process performed by the first motion detection section 130. FIG. [Figure 11] 10 is a flowchart showing a signal processing operation by the signal processing system 101 of the second embodiment. [Figure 12] 13 is a flowchart showing an operation of a first motion detection process by a first motion detection section 130 of the second embodiment. [Figure 13] FIG. 13 is a block diagram showing an example of the configuration of a signal processing system according to a third embodiment of the present invention. [Figure 14] 13 is a flowchart showing a signal processing operation by the signal processing system 102 of the third embodiment. [Figure 15] 13 is a flowchart showing the operation of a second motion detection process by a second motion detection section 140 of the third embodiment. [Figure 16] FIG. 1 is an explanatory diagram showing an example of a hardware configuration of a signal processing system according to the present invention; [Figure 17] 1 is a block diagram showing an overview of a signal processing system according to the present invention; DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0015] First, the problem to be solved by the present invention will be described.

[0016] In this specification, a state in which only objects that are constantly present, such as buildings, exist in the area to be analyzed is called a "steady state." Note that "constantly existing" means that the object exists throughout the monitoring period.

[0017] In image analysis, background subtraction detection technology and anomaly detection technology are known as technologies for detecting objects (vehicles, aircraft, etc.) other than permanently existing objects such as buildings, and for detecting ground conditions such as the construction or collapse of buildings.

[0018] The above-mentioned technology is realized by selecting or generating image data that indicates a steady state from image data stored in the past, and detecting changes from the image to be analyzed.

[0019] A SAR (Synthetic Aperture Radar) image is a complex image that has information on the reflection intensity and phase of irradiated microwaves for each pixel. Coherent change detection technology is one of the change detection techniques for complex images.

[0020] Coherent change detection technology is a technology that can detect minute changes from a steady state based on the value of the complex correlation coefficient (coherence), which indicates the similarity between images. Coherence, which is the complex correlation coefficient between SAR images, is an index that indicates the "correlation of intensity and phase in a local area" between SAR images. When a method that uses coherence to detect changes is used, phase information is used in addition to intensity information, which increases the sensitivity of change detection.

[0021] Figure 1 is an explanatory diagram showing the relationship between the coherence value and the correlation between the reflection intensity and phase between SAR images. As shown in Figure 1, when the coherence value is high, the similarity of both the reflection intensity and the phase between SAR images is high. In other words, there is almost no change between the SAR images.

[0022] Furthermore, as shown in Figure 1, when the coherence value is low, at least one of the similarity of the reflection intensity and the similarity of the phase between the SAR images is low, i.e., there is a change between the SAR images.

[0023] In addition, the coherence value is an index that is more sensitive to changes in phase than to changes in the reflection intensity of the reflected waves. As shown in Figure 1, the coherence value is lower when the phase similarity is lower than the reflection intensity similarity. Coherent change detection technology can also detect the replacement of reflectors.

[0024] The problem that the present invention seeks to solve is to generate a complex image that exhibits a steady state suitable for SAR image analysis.

[0025] SAR images observed by SAR satellites orbiting the Earth are taken under different shooting conditions for each observation (for example, the position of the satellite at the time of observation). Therefore, even when the same steady state is observed, the SAR images obtained for each observation differ. In particular, in areas with buildings with different heights, such as urban areas, phase information changes significantly for each observation. Therefore, unless complex images that show the steady state according to each shooting condition can be generated, changes in the image due to differences in shooting conditions will be interpreted as changes occurring within the area being analyzed, which will lead to false detection.

[0026] When the shooting conditions are different, even if the steady state is the same, one of the reasons why the SAR images observed under each observation condition differ is the height of the structure. Figure 2 is an explanatory diagram showing an example of a SAR satellite photographing a structure. A SAR satellite is an artificial satellite equipped with a SAR.

[0027] The shooting conditions are different between Observation 1 and Observation 2 shown in Figure 2. The amount of phase change, which depends on the height of the building, is different between Observation 1 and Observation 2. Therefore, even in the same steady state, the phase of the observed SAR images is different.

[0028] Another reason why SAR images observed under different shooting conditions differ even under the same steady state is the reflection intensity of overlapping buildings. Figure 3 is an explanatory diagram showing an example of the layover phenomenon that occurs in SAR images.

[0029] As shown in Figure 3, when distance SA<distance SB, the position A of the building and the position B of the house are reversed on the image. The position reversal phenomenon shown in Figure 3 is the layover phenomenon.

[0030] When a SAR satellite captures a steady state image under conditions that cause the layover phenomenon, it captures a two-dimensional image (SAR image) in which buildings and houses overlap, as shown in Figure 3. The area in the two-dimensional image in Figure 3 where buildings and houses overlap is a layover area, where signals received from multiple reflectors overlap. A layover area is an area in which the information of multiple buildings overlaps, making it difficult to extract information about each individual building.

[0031] In layover areas, the phase of the SAR image obtained for each observation also depends on the reflection intensity of overlapping buildings. Since the overlapping of buildings differs depending on the shooting conditions, the phase of the observed SAR image will differ even in the same steady state.

[0032] Due to the above two factors, even if the SAR satellite observes a steady state, the observed SAR images may differ. In other words, the amplitude and phase of constantly existing objects such as buildings recorded in SAR images depend on the shooting conditions of the SAR images.

[0033] As mentioned above, even if a steady state is captured by SAR, the SAR images observed under different capture conditions differ greatly, making it difficult to estimate a complex image that shows the steady state for each capture condition.

[0034] If it is not possible to estimate a complex image that shows a steady state that matches each shooting condition, it is difficult to detect changes in the SAR image to be analyzed using coherent change detection technology that uses phase information. In particular, in areas with tall man-made structures such as urban areas, the layover phenomenon that is specific to SAR images is likely to occur, making it even more difficult to estimate a complex image that shows a steady state that matches each shooting condition.

[0035] As a method for calculating correlation using phase information other than the coherence value, for example, there is a method for extracting phase information from SAR images as real values ​​and calculating correlation using the extracted real values.

[0036] Hereinafter, embodiments of the present invention that solve the problem of generating a complex image showing a steady state suitable for SAR image analysis will be described with reference to the drawings.

[0037] Embodiment 1. [Configuration Description] A first embodiment of the present invention will now be described with reference to the drawings. Fig. 4 is a block diagram showing an example of the configuration of a signal processing system according to the first embodiment of the present invention.

[0038] The signal processing system 100 of this embodiment generates a simulated SAR image from a group of accumulated observed SAR images.

[0039] The simulated SAR image of this embodiment refers to a two-dimensional image in which the reconstructed three-dimensional information of the area to be analyzed (data having information on reflection intensity and phase at each three-dimensional position in a steady state) is simulated as reflection intensity and phase information predicted to be observed when the SAR image to be analyzed is captured under the same capturing conditions as the SAR image to be analyzed, i.e., a complex image showing a steady state suitable for the capturing conditions of the SAR image to be analyzed.

[0040] The SAR image to be analyzed is an image acquired by a SAR satellite, and is the SAR image to which change detection is to be applied. In other words, the simulated SAR image is a complex image that shows a steady state that is suited to the shooting conditions of the SAR image to be analyzed.

[0041] As shown in Fig. 4, the signal processing system 100 includes a three-dimensional information reconstruction unit 110 and a simulated SAR image generation unit 120. Also, as shown in Fig. 4, the signal processing system 100 is communicably connected to a SAR image storage unit 200.

[0042] When the three-dimensional information reconstruction unit 110 is included in a system other than the signal processing system 100, the signal processing system 100 may include only the simulated SAR image generation unit 120.

[0043] The SAR image storage unit 200 has a function of storing one or more observed SAR images. The SAR image storage unit 200 may be included in the signal processing system 100.

[0044] The three-dimensional information reconstruction unit 110 receives a group of observed SAR images stored in the SAR image storage unit 200. The input observed SAR images are complex images having information on the reflection intensity and phase of irradiated microwaves for each pixel, including information on the shooting conditions indicating the position of the SAR satellite at the time of observation, the coordinates of the area to be analyzed, and the resolution, etc. Note that the three-dimensional information reconstruction unit 110 is not limited to observation SAR images obtained by observing a steady state, and may also include observation SAR images obtained by photographing a case where there is a change from the steady state in the area to be analyzed.

[0045] The three-dimensional information reconstruction unit 110 has a function of reconstructing and outputting three-dimensional information of the region to be analyzed (data having information on reflection intensity and phase information at each three-dimensional position in a steady state). Specifically, the three-dimensional information output by the three-dimensional information reconstruction unit 110 may be a three-dimensional complex reflection intensity distribution having information on reflection intensity and phase, or may be three-dimensional point cloud data that is a collection of points having information on reflection intensity and phase. The output three-dimensional information may have information on temperature, displacement, etc. in addition to information on reflection intensity and phase.

[0046] SAR tomography is one method for reconstructing 3D information in the 3D information reconstruction unit 110. SAR tomography is a technique for estimating the complex reflection intensity distribution in the elevation direction for each pixel using multiple observed SAR images. Here, the elevation direction represents the direction perpendicular to the azimuth-range plane (the plane formed by the traveling direction of the SAR satellite and the line of sight).

[0047] FIG. 5 shows the azimuth-range position (x → 1 is an explanatory diagram showing an example of a method for estimating a complex reflection intensity distribution at a pixel corresponding to

[0048] In addition, symbols such as "→" used in the text in this specification should be written directly above the character immediately preceding it, but due to limitations in text notation, they are written immediately after the character in question as shown above.

[0049] In FIG. 5, s represents the elevation direction. In FIG. 5, the direction perpendicular to the direction s represents the azimuth-range plane. Also, the azimuth-range position (x → ) is the elevator in Figure 5. It is the intersection of the axis indicating the orientation direction and the axis indicating the line of sight of the satellite.

[0050] The three-dimensional information reconstruction unit 110 estimates, for each pixel, a complex reflection intensity distribution that indicates the height, reflection intensity, and phase of a building that constantly exists over an observation period, based on a plurality of observed SAR images.

[0051] When SAR tomography is used in the three-dimensional information reconstruction unit 110, a three-dimensional complex reflection intensity distribution is generated by combining the complex reflection intensities obtained for each pixel for all pixels in the area to be analyzed.

[0052] The reason why the observed SAR images are input to the 3D information reconstruction unit 110 is that in order to reconstruct a 3D steady state using SAR tomography or the like, multiple observed SAR images taken from slightly different orbits are required.

[0053] The upper part of Fig. 5 shows the first through Nth observations by the SAR satellite, where N represents the total number of observations and is an integer greater than 1.

[0054] The first to Nth observations shown in FIG. 5 correspond to a synthetic aperture in the elevation direction. In the nth (where 1≦n≦N) observation, the azimuth-range position (x → ) The relationship between the received signal (complex signal) recorded in the corresponding pixel and the complex reflection intensity distribution at that pixel is given by the following equation (1).

[0055]

number

[0056] g in Equation (1) obs (x → ,n) is the azimuth-range position (x → ) represents the received signal (complex signal) recorded at the pixel corresponding to the → (x → ,n) is the azimuth-range position (x → ) represents the steering vector at the pixel corresponding to the Alpha in → (x → ,n) is the azimuth-range position (x → ) Represents the degree distribution.

[0057] The steering vector is obtained from the shooting conditions. For example, the steering vector r → (x → , n) is expressed by the following equation (2).

[0058]

number

[0059] In addition, k in equation (2) n represents the phase-altitude conversion coefficient (coefficient for converting between phase and altitude). Also, s in equation (2) l(l=1, ,L) represents the position in the elevation direction. The steering vector may be expressed by an equation other than equation (2). For example, a steering vector that takes into account the effects of temperature and displacement may be used. In addition, j in equation (2) represents the imaginary unit. In addition, π in equation (2) represents the constant pi.

[0060] A relational expression such as Equation (1) is determined for each of the 1st to Nth observations. The 3D information reconstruction unit 110 calculates the azimuth-range position (x → ) at the pixel corresponding to Complex reflection intensity distribution α of buildings bg → (x → ) is obtained.

[0061] That is, the three-dimensional information reconstruction unit 110 determines the complex reflection intensity distribution so that the N observation data in which the area including the building and the like is photographed matches the N steering vectors, thereby obtaining the complex reflection intensity distribution α bg → (x → ) is obtained.

[0062] The lower part of FIG. 5 shows the azimuth-range position (x → ) The complex reflectance intensity distribution α of a permanently existing building at the pixel bg → (x → ) absolute value of |α bg Here is an example of | absolute value |α bg corresponds to the reflection intensity on the vertical axis shown in Fig. 5. The horizontal axis shown in Fig. 5 indicates the elevation position.

[0063] The azimuth-range position (x → ) Permanent structures in pixels corresponding to Complex reflection intensity distribution α of object bg → (x →) is the elevation position s l1 (ground), s l2 (house), s l3 (building) shows high value. That is, position x → The received signal at Position s l1 , s l2 , s l3 More precisely, the complex reflection intensity at position x → The received signal at is the complex reflection intensity distribution in the elevation direction. This corresponds to the result of the Fourier transform of

[0064] When SAR tomography is used in the three-dimensional information reconstruction unit 110, the three-dimensional information reconstruction unit 110 outputs a three-dimensional complex reflection intensity distribution as three-dimensional information by combining the complex reflection intensity distribution for each pixel obtained by solving the optimization problem for all pixels in the area to be analyzed. The three-dimensional information reconstruction unit 110 is not limited to the above three-dimensional complex reflection intensity distribution, and may output three-dimensional point cloud data, which is a set of points each having information on the position, reflection intensity, and phase of a reflector, as the three-dimensional information.

[0065] The three-dimensional information (data having information on reflection intensity and phase at each three-dimensional position in a steady state) reconstructed by the three-dimensional information reconstruction unit 110 is input to the simulated SAR image generation unit 120. The three-dimensional information input to the simulated SAR image generation unit 120 may have information on temperature, displacement, etc. in addition to the information on reflection intensity and phase.

[0066] The shooting conditions of one or more SAR images to be analyzed are also input to the simulated SAR image generating unit 120. The one or more SAR images to be analyzed may be one or more observation SAR images selected from the group of observation SAR images stored in the SAR image storage unit 200, or may be one or more newly acquired observation SAR images. The multiple SAR images to be analyzed may be multiple observation SAR images that are a mixture of stored observation SAR images and acquired observation SAR images.

[0067] The shooting conditions of the SAR image to be analyzed and input to the simulated SAR image generation unit 120 are not limited to the shooting conditions of the observed SAR image used to reconstruct the three-dimensional information in the three-dimensional information reconstruction unit 110, but may be the shooting conditions of one or more newly acquired observed SAR images.

[0068] The shooting conditions input to the simulated SAR image generating unit 120 include the position of the SAR satellite at the time of observation, the coordinates of the area to be analyzed, the resolution, etc. The shooting conditions input may be the shooting conditions of the observed SAR image stored in the SAR image storage unit 200, or may be the shooting conditions of a newly acquired observed SAR image.

[0069] The simulated SAR image generating unit 120 has a function of performing simulated observation using the reconstructed three-dimensional information (data having information on reflection intensity and phase information at each three-dimensional position in a steady state) and the imaging conditions of the SAR image(s) to be analyzed. Specifically, the simulated SAR image generating unit 120 generates a simulated SAR image, which is a complex image showing a steady state suitable for the imaging conditions of the SAR image(s) to be analyzed.

[0070] The simulated SAR image generating unit 120 performs simulated observation for each imaging condition of the SAR image(s) to be analyzed. After performing the simulated observation one or more times, the simulated SAR image generating unit 120 outputs simulated SAR image(s) corresponding to each of the one or more imaging conditions acquired.

[0071] The signal processing system 100 of this embodiment utilizes data having information on reflection intensity and phase at each three-dimensional position in a steady state, i.e., three-dimensional information, and therefore can generate a simulated SAR image, which is a complex image showing a steady state that matches the shooting conditions of the SAR image(s) to be analyzed.

[0072] As described above, the three-dimensional information reconstruction unit 110 of the signal processing system 100 calculates three-dimensional information using observed SAR images of an area photographed by SAR.

[0073] Furthermore, the simulated SAR image generating unit 120 of the signal processing system 100 generates a simulated SAR image, which is a complex image showing a steady state suitable for the imaging conditions of the SAR image to be analyzed, by using three-dimensional information, which is data having information on reflection intensity and phase information at three-dimensional positions in a steady state in which an area is reconstructed using the observation SAR images captured by SAR, and the imaging conditions of the SAR image to be analyzed.

[0074] [Explanation of operation] An operation of generating a simulated SAR image by the signal processing system 100 of this embodiment will be described below with reference to Fig. 6. Fig. 6 is a flowchart showing the signal processing operation by the signal processing system 100 of the first embodiment.

[0075] First, the three-dimensional information reconstruction unit 110 of the signal processing system 100 executes three-dimensional information reconstruction processing (step S110). The three-dimensional information reconstruction processing is processing for reconstructing three-dimensional information of a region to be analyzed based on a group of accumulated observation SAR images.

[0076] Next, the simulated SAR image generating unit 120 of the signal processing system 100 executes a simulated SAR image generating process (step S120). The simulated SAR image generating process is a process for generating simulated SAR image(s) which are image(s) in which simulated received signals when observed under the same shooting conditions as the respective SAR image(s) to be analyzed are recorded, based on the shooting conditions of the SAR image(s) to be analyzed and the reconstructed three-dimensional information.

[0077] After performing the simulated SAR image generation process, the signal processing system 100 ends the signal processing.

[0078] Next, the 3D information reconstruction process in step S110, which is a sub-process constituting the signal processing shown in Fig. 6, will be described with reference to Fig. 7. Fig. 7 is a flowchart showing the operation of the 3D information reconstruction process by the 3D information reconstruction unit 110 of the first embodiment.

[0079] First, the three-dimensional information reconstruction unit 110 calculates a steering vector r from each of the imaging conditions of the accumulated observation SAR image group. → (x → , n) is derived (step S111).

[0080] Next, the three-dimensional information reconstruction unit 110 selects one pixel for which the complex reflection intensity distribution has not yet been calculated from among the pixels of the accumulated observed SAR images, that is, enters into a pixel loop (step S112).

[0081] The three-dimensional information reconstruction unit 110 uses the received signals at selected pixels of the accumulated observed SAR images and the steering vectors for each of the observed SAR images to reconstruct a complex reflection intensity distribution α bg → (x → In step S113, the position x → Corresponding to The complex reflection intensity distribution α bg → (x → ) is calculated.

[0082] The three-dimensional information reconstruction unit 110 repeats the process of step S113 while there are pixels in the accumulated observation SAR images for which the complex reflection intensity distribution has not been calculated. When the complex reflection intensity distributions of all pixels in the observation SAR images have been calculated, the three-dimensional information reconstruction unit 110 exits the pixel loop (step S114). When the three-dimensional information reconstruction unit 110 exits the pixel loop, the three-dimensional information of the target area is reconstructed.

[0083] After exiting the pixel loop, the three-dimensional information reconstruction unit 110 outputs the calculated three-dimensional complex reflection intensity distribution as data having information on reflection intensity and phase at each three-dimensional position in a steady state, i.e., three-dimensional information. The output three-dimensional information may be the above-mentioned three-dimensional complex reflection intensity distribution, or may be three-dimensional point cloud data that is a set of points having information on reflection intensity and phase (step S115). After outputting the three-dimensional information, the three-dimensional information reconstruction unit 110 ends the three-dimensional information reconstruction process.

[0084] Next, the simulated SAR image generation process in step S120, which is a sub-process constituting the signal processing shown in Fig. 6, will be described with reference to Fig. 8. Fig. 8 is a flowchart showing the operation of the simulated SAR image generation process by the simulated SAR image generating unit 120 of the first embodiment.

[0085] First, the simulated SAR image generator 120 calculates a steering vector r from each of the imaging conditions of all input SAR images to be analyzed. → (x → , n) is derived (step S121).

[0086] Next, the simulated SAR image generating unit 120 selects one imaging condition for which a simulated SAR image has not yet been generated from among the imaging conditions of the input SAR image(s) to be analyzed, i.e., enters into an imaging condition loop (step S122).

[0087] Next, the simulated SAR image generating unit 120 selects one pixel for which a simulated complex signal has not yet been calculated from among the pixels of the observed SAR image(s) corresponding to the selected imaging condition, i.e., enters into a pixel loop (step S123).

[0088] The simulated SAR image generator 120 generates the input complex reflection intensity distribution α bg → (x → ) and the steering vector r corresponding to the selected imaging condition → (x → , n) to find the position x corresponding to the selected pixel. → A simulated complex signal g sim (x → , n) (step S124). The simulated SAR image generating unit 120 calculates the simulated complex signal according to, for example, the following equation (3).

[0089]

number

[0090] The simulated SAR image generating unit 120 may calculate the simulated complex signal according to an equation other than equation (3). In step S124, the position x → A simulated complex signal g at sim (x → ,n) is calculated.

[0091] The simulated SAR image generating unit 120 repeats the process of step S124 while there are pixels for which the simulated complex signals have not been calculated among the pixels of the observed SAR image corresponding to the selected imaging condition. When the simulated complex signals of all pixels in the observed SAR image have been calculated, the simulated SAR image generating unit 120 exits the pixel loop (step S125).

[0092] The simulated SAR image generating unit 120 repeats the processes of steps S123 to S125 while there are imaging conditions for which no simulated SAR image has been generated among the imaging conditions of the input SAR image(s) to be analyzed. When simulated SAR images have been generated for all imaging conditions for the SAR image(s) to be analyzed, the simulated SAR image generating unit 120 exits the imaging condition loop (step S126).

[0093] When the simulated SAR image generation unit 120 exits the shooting condition loop, the processing of step S124 is executed for all positions under all shooting conditions of the input SAR image(s) to be analyzed, and a group of simulated SAR images of the target area is generated.

[0094] After exiting the imaging condition loop, the simulated SAR image generating unit 120 outputs a simulated SAR image which is a complex image showing a steady state suitable for the imaging conditions of the input SAR image to be analyzed. When the imaging conditions of the SAR image group to be analyzed are input, the simulated SAR image generating unit 120 outputs a simulated SAR image group which is a complex image showing a steady state suitable for each imaging condition of the input SAR image group to be analyzed (step S127). After outputting the simulated SAR image(s), the simulated SAR image generating unit 120 ends the simulated SAR image generation process.

[0095] [Effect description] The three-dimensional information reconstruction unit 110 of the signal processing system 100 of this embodiment reconstructs data having information on reflection intensity and phase at each three-dimensional position in the steady state of the area to be analyzed, i.e., three-dimensional information, based on the accumulated observed SAR images. Also, the simulated SAR image generation unit 120 generates simulated SAR image(s) based on the shooting conditions of the SAR image(s) to be analyzed and the reconstructed three-dimensional information.

[0096] The advantage of using SAR tomography is that simulated complex signals that indicate the reflection intensity and phase of each overlapping reflector are recorded in the simulated SAR image. Even if a digital elevation model (DEM) is used, it is difficult to generate simulated complex signals that accurately indicate the reflection intensity and phase of each overlapping reflector. Therefore, users who perform coherent change detection using the generated simulated SAR image can robustly detect changes even in layover areas.

[0097] In this embodiment, the three-dimensional information reconstruction unit 110 uses SAR tomography as a means for calculating three-dimensional information. However, the three-dimensional information reconstruction unit 110 may use other means than SAR tomography as a means for calculating three-dimensional information that can reproduce reflection intensity and phase.

[0098] Embodiment 2. [Configuration Description] Next, a second embodiment of the present invention will be described with reference to the drawings. Fig. 9 is a block diagram showing an example of the configuration of a signal processing system according to the second embodiment of the present invention.

[0099] As shown in Fig. 9, the signal processing system 101 includes a three-dimensional information reconstruction unit 110, a simulated SAR image generation unit 120, and a first motion detection unit 130. Also, as shown in Fig. 9, the signal processing system 101 is communicably connected to a SAR image storage unit 200.

[0100] The functions of the three-dimensional information reconstruction unit 110 and the simulated SAR image generation unit 120 in this embodiment are similar to the functions in the first embodiment.

[0101] The first movement detection unit 130 receives simulated SAR image(s) corresponding to all of the shooting conditions of the SAR image(s) to be analyzed input to the simulated SAR image generation unit 120 from the simulated SAR image generation unit 120. The first movement detection unit 130 also receives the SAR image(s) to be analyzed. The SAR image(s) to be analyzed include received signals indicating information on reflection intensity and phase.

[0102] The first change detection unit 130 has a function of outputting, as a detection result, a value calculated by correlation processing using phase information of the simulated SAR image and phase information of the SAR image to be analyzed, or a determination result of the presence or absence of a change by threshold processing.

[0103] The correlation may simply represent the degree of similarity between the SAR image to be analyzed and the simulated SAR image (hereinafter referred to as "similarity"). The similarity is, for example, the distance between multiple images. The similarity may also be represented by an index other than the distance between multiple images. For convenience, the similarity will be referred to as correlation below.

[0104] 10 is an explanatory diagram showing a specific example of the first motion detection process by the first motion detection section 130. As described in the first embodiment, the 3D information reconstruction section 110 reconstructs 3D information using the observed SAR images stored in the SAR image storage section 200 as input. Next, the 3D information reconstruction section 110 outputs the reconstructed 3D information.

[0105] Moreover, the imaging conditions of the SAR image to be analyzed and the reconstructed three-dimensional information are input to the simulated SAR image generating unit 120. The simulated SAR image generating unit 120 uses the input imaging conditions to generate a complex image showing a steady state suited to each imaging condition, i.e., a simulated SAR image.

[0106] The first change detection unit 130 of this embodiment receives the SAR image to be analyzed that is input to the simulated SAR image generation unit 120, and the simulated SAR image generated by the simulated SAR image generation unit 120. The first change detection unit 130 detects whether or not a change from a steady state has occurred between the input SAR image to be analyzed and the simulated SAR image.

[0107] For example, the first motion detection unit 130 detects the positions x → In this case, the coherence value γ(x → ) is calculated. As mentioned above, the change from the steady state If it is not, the calculated coherence value will be high, and if it is varying from the steady state, the calculated coherence value will be low.

[0108] As shown in FIG. 10, the first motion detection unit 130 detects, for example, each position x → The results obtained in Heath value γ(x → ) is illustrated in two dimensions. If the change includes a part that has changed, the change will be detected as a decrease in the coherence value.

[0109] Furthermore, as described in the first embodiment, when a simulated SAR image is used, changes are robustly detected even in a layover area. Therefore, as shown in Fig. 10, the first motion detection unit 130 can identify a motion detection point in a layover area. Note that the dashed frame in the motion detection result shown in Fig. 10 corresponds to the layover area.

[0110] Note that first change detection section 130 may output the value itself calculated by correlation processing using phase information, or may output the result of determining whether or not there is a change by threshold processing.

[0111] As described above, the first change detection section 130 of the signal processing system 101 detects changes that have occurred in areas of the SAR image to be analyzed by comparing the SAR image to be analyzed with the simulated SAR image.

[0112] For example, the first change detection unit 130 detects a change by calculating the degree of similarity between the SAR image to be analyzed and the simulated SAR image. The first change detection unit 130 may calculate the degree of similarity using phase information indicated by the SAR image to be analyzed and phase information indicated by the simulated SAR image. The degree of similarity may also be a coherence value.

[0113] [Explanation of operation] Hereinafter, the operation of identifying a change detection point of the signal processing system 101 of this embodiment will be described with reference to Fig. 11. Fig. 11 is a flowchart showing the signal processing operation by the signal processing system 101 of the second embodiment.

[0114] First, the three-dimensional information reconstruction unit 110 of the signal processing system 101 executes three-dimensional information reconstruction processing (step S210). The three-dimensional information reconstruction processing in step S210 is similar to the three-dimensional information reconstruction processing in step S110.

[0115] Next, the simulated SAR image generating unit 120 of the signal processing system 101 executes a simulated SAR image generating process (step S220). The simulated SAR image generating process in step S220 is similar to the simulated SAR image generating process in step S120.

[0116] Next, the first change detection section 130 of the signal processing system 101 executes a first change detection process (step S230). The first change detection process is a process for detecting a change by executing a correlation process using phase information.

[0117] After executing the first motion detection process, the signal processing system 101 ends the signal processing.

[0118] Next, the first motion detection process of step S230, which is a sub-process constituting the signal processing shown in Fig. 11, will be described with reference to Fig. 12. Fig. 12 is a flowchart showing the operation of the first motion detection process by the first motion detection section 130 of the second embodiment.

[0119] First, the first motion detection unit 130 selects one pixel for which correlation has not yet been calculated from among the pixels of the simulated SAR image, that is, enters a pixel loop (step S231).

[0120] The first motion detection unit 130 calculates the correlation, at the selected pixel, between the SAR image to be analyzed and the simulated SAR image generated under the same shooting conditions as the SAR image to be analyzed (step S232).

[0121] Specifically, the first motion detection unit 130 detects a complex signal g obs (x → ,n) and the simulation images generated under the same shooting conditions as the SAR images to be analyzed. The simulated complex signal g at a selected pixel of the pseudo-SAR image sim (x → ,n) and phase information is used. The correlation is calculated.

[0122] For example, the first change detection section 130 may use a coherence value calculated by the following equation (4) for calculating the correlation.

[0123]

number

[0124] In addition, E(·) in equation (4) represents an expected value. Furthermore, first change detection section 130 may employ a value calculated by correlation processing using phase information, other than the coherence value.

[0125] The first motion detection unit 130 repeats the process of step S232 while there are pixels in the simulated SAR image for which correlation has not been calculated. When correlations have been calculated for all pixels in the simulated SAR image, the first motion detection unit 130 exits the pixel loop (step S233).

[0126] After exiting the pixel loop, first motion detection unit 130 outputs a detection result including the calculated correlations, etc. (Step S234). After outputting the detection result, first motion detection unit 130 ends the first motion detection process.

[0127] When the group of simulated SAR images is input, the first motion detection unit 130 performs the first motion detection process in step S230 for each of the input simulated SAR images.

[0128] [Effect description] The first change detection unit 130 of the signal processing system 101 of this embodiment calculates the correlation between the SAR image to be analyzed and the simulated SAR image generated under the same shooting conditions as the SAR image to be analyzed, using phase information. By referring to the correlation calculated using the phase information, the user can easily detect a change from a steady state. Furthermore, by the first change detection unit 130 calculating the correlation between the simulated SAR image and the SAR image to be analyzed, the user can robustly detect changes even in a layover area.

[0129] Furthermore, as shown in FIG. 10, when first motion detection section 130 projects the result of motion detection onto a two-dimensional map, the user can easily identify the location where motion has been detected.

[0130] Furthermore, even if multiple changes occur in the target area over the observation period, the first change detection unit 130 can detect each change as a change from the steady state by calculating the correlation between each of the multiple SAR images to be analyzed and the corresponding simulated SAR image.

[0131] When multiple motion detection results are obtained as described above, if first motion detection section 130 displays the multiple motion detection results in chronological order, the user can easily identify each motion detection location and each motion detection time.

[0132] Embodiment 3. [Configuration Description] Next, a third embodiment of the present invention will be described with reference to the drawings. Fig. 13 is a block diagram showing an example of the configuration of a signal processing system according to the third embodiment of the present invention.

[0133] As shown in Fig. 13, the signal processing system 102 includes a three-dimensional information reconstruction unit 110, a simulated SAR image generation unit 120, and a second motion detection unit 140. Also, as shown in Fig. 13, the signal processing system 102 is communicably connected to a SAR image storage unit 200.

[0134] The functions of the three-dimensional information reconstruction unit 110 and the simulated SAR image generation unit 120 in this embodiment are similar to the functions in the first embodiment.

[0135] In this embodiment, shooting conditions of the SAR image group to be analyzed are input to the simulated SAR image generating unit 120. Moreover, the simulated SAR image generating unit 120 outputs a simulated SAR image group corresponding to all shooting conditions of the SAR image group to be analyzed input to the simulated SAR image generating unit 120.

[0136] The second movement detection unit 140 receives, from the simulated SAR image generation unit 120, a group of simulated SAR images corresponding to all of the shooting conditions of the group of SAR images to be analyzed that have been input to the simulated SAR image generation unit 120. The group of SAR images to be analyzed is also input to the second movement detection unit 140. The SAR images to be analyzed include received signals that indicate information on reflection intensity and phase.

[0137] The second change detection unit 140 performs correlation processing using phase information for each pair of the SAR image to be analyzed and a simulated SAR image corresponding to the SAR image to be analyzed, and outputs as a detection result a statistical amount obtained from each value calculated for each pair, or a determination result of the presence or absence of a change based on threshold processing.

[0138] A correlation process using phase information is performed for each pair of a SAR image to be analyzed and a simulated SAR image that corresponds to the SAR image to be analyzed, and statistics obtained from the values ​​calculated for each pair include, for example, the average or median of the values ​​calculated by the correlation process using the phase information.

[0139] As described above, the simulated SAR image generating unit 120 of the signal processing system 102 generates a simulated SAR image for each of the shooting conditions of the SAR images to be analyzed. In addition, the second change detection unit 140 calculates the degree of similarity across multiple pairs of the SAR image to be analyzed and the simulated SAR image, and detects changes using the calculated degrees of similarity.

[0140] Note that, instead of second motion detection section 140, signal processing system 102 of this embodiment may include first motion detection section 130 which further has the functions of second motion detection section 140.

[0141] [Explanation of operation] Hereinafter, the operation of identifying a change detection point of the signal processing system 102 of this embodiment will be described with reference to Fig. 14. Fig. 14 is a flowchart showing the signal processing operation by the signal processing system 102 of the third embodiment.

[0142] First, the three-dimensional information reconstruction unit 110 of the signal processing system 102 executes three-dimensional information reconstruction processing (step S310). The three-dimensional information reconstruction processing in step S310 is similar to the three-dimensional information reconstruction processing in step S110.

[0143] Next, the simulated SAR image generating unit 120 of the signal processing system 102 executes a simulated SAR image generating process (step S320). The simulated SAR image generating process in step S320 is similar to the simulated SAR image generating process in step S120.

[0144] Next, the second change detection unit 140 of the signal processing system 102 executes a second change detection process (step S330). The second change detection process is a process that executes correlation processing using phase information multiple times and detects changes by utilizing statistics obtained from the multiple calculated correlations.

[0145] After performing the second motion detection process, the signal processing system 102 ends the signal processing.

[0146] Next, the second motion detection process of step S330, which is a sub-process constituting the signal processing shown in Fig. 14, will be described with reference to Fig. 15. Fig. 15 is a flowchart showing the operation of the second motion detection process by the second motion detection section 140 of the third embodiment.

[0147] The second motion detection unit 140 calculates correlation between the SAR images to be analyzed and the simulated SAR images generated under the same imaging conditions as those of the SAR images to be analyzed (step S331). For example, the second motion detection unit 140 executes correlation processing using phase information multiple times for each pair of the SAR image to be analyzed and the simulated SAR image.

[0148] Next, the second motion detection unit 140 performs correlation processing using phase information for each pair of the SAR image to be analyzed and the simulated SAR image corresponding to the SAR image to be analyzed, and calculates statistics obtained from each value calculated for each pair (step S332). For example, the second motion detection unit 140 calculates statistics such as an average from the multiple correlations calculated in step S331.

[0149] Next, second motion detection section 140 outputs the detection result including the calculated statistics etc. (Step S333). After outputting the detection result, second motion detection section 140 ends the second motion detection process.

[0150] [Effect description] The second change detection unit 140 of the signal processing system 102 of this embodiment performs correlation processing using phase information for each pair of a SAR image to be analyzed and a simulated SAR image corresponding to the SAR image to be analyzed, and outputs the statistics obtained from each value calculated for each pair, or the result of determining whether or not there is a change by determining the statistics against a threshold. When statistics are used, it becomes possible to evaluate not only the level of a single correlation value but also the difference of each correlation from a typical value (for example, the average value), thereby improving the robustness of change detection.

[0151] The signal processing systems 101-102 of the respective embodiments are used to detect changes that occur in urban areas without people actually visiting the areas. The signal processing systems 101-102 are also used to quickly detect when and where a change occurs in an area that is regularly monitored.

[0152] It is also assumed that the signal processing systems 101-102 of the respective embodiments are applied to the monitoring of military bases and cities in areas of concern from the viewpoint of security, because a user of the signal processing systems 101-102 can quickly detect the appearance of aircraft or vehicles in the monitored area simply by comparing the SAR image to be analyzed with the simulated SAR image.

[0153] Furthermore, the three-dimensional information estimated by the three-dimensional information reconstruction unit 110 using SAR tomography may be stored in a server or the like. When the three-dimensional information is stored in advance in a server or the like, the user of the signal processing system 100 to 102 can generate a simulated SAR image for the area in which changes are to be detected. In other words, the user himself / herself does not need to reconstruct the three-dimensional information.

[0154] Furthermore, for example, when creating training data for object detection in SAR images using machine learning, if the output of the first change detection unit 130 is added to the machine learning, the object positions added to the training data are limited to the output area of ​​the first change detection unit 130. In other words, the range of annotation is narrowed, and the cost required for learning is reduced.

[0155] A specific example of the hardware configuration of the signal processing systems 100 to 102 of the respective embodiments will be described below. Fig. 16 is an explanatory diagram showing an example of the hardware configuration of a signal processing system according to the present invention.

[0156] The signal processing system shown in FIG. 16 includes a CPU (Central Processing Unit) 11 and a main processor. The system includes a memory unit 12, a communication unit 13, and an auxiliary memory unit 14. The system also includes an input unit 15 for user operation, and an output unit 16 for presenting the user with the processing results or the progress of the processing contents.

[0157] The signal processing system is realized by software, in which the CPU 11 shown in FIG. 16 executes a program that provides the functions of each component.

[0158] That is, the CPU 11 loads a program stored in the auxiliary storage unit 14 into the main storage unit 12, executes it, and controls the operation of the signal processing system, whereby each function is realized by software.

[0159] 16 may include a DSP (Digital Signal Processor) instead of the CPU 11. Alternatively, the signal processing system shown in FIG 16 may include both the CPU 11 and a DSP.

[0160] The main memory unit 12 is used as a working area for data and a temporary storage area for data. The main memory unit 12 is, for example, a RAM (Random Access Memory).

[0161] The communication unit 13 has a function of inputting and outputting data to and from peripheral devices via a wired network or a wireless network (information and communication network).

[0162] The auxiliary storage unit 14 is a non-transient tangible storage medium. Examples of non-transient tangible storage media include magnetic disks, magneto-optical disks, and CD-ROMs (Compact Disk Read Only Examples of memory devices include digital versatile disk read only memory (DVD-ROM), digital versatile disk read only memory (DVD-ROM), and semiconductor memory.

[0163] The input unit 15 has a function of inputting data and processing commands, and is, for example, an input device such as a keyboard or a mouse.

[0164] The output unit 16 has a function of outputting data, and is, for example, a display device such as a liquid crystal display device, or a printing device such as a printer.

[0165] As shown in FIG. 16, in the signal processing system, each component is connected to a system bus 17 .

[0166] In the signal processing system 100 of the first embodiment, the auxiliary storage unit 14 stores programs for implementing a three-dimensional information reconstruction unit 110 and a simulated SAR image generation unit 120 .

[0167] The signal processing system 100 may be implemented with a circuit including hardware components such as an LSI (Large Scale Integration) that realizes the functions shown in FIG. stomach.

[0168] In the signal processing system 101 of the second embodiment, the auxiliary storage unit 14 stores programs for implementing the three-dimensional information reconstruction unit 110, the simulated SAR image generation unit 120, and the first motion detection unit .

[0169] The signal processing system 101 may be implemented with a circuit including hardware components such as an LSI that realizes the functions shown in FIG.

[0170] In the signal processing system 102 of the third embodiment, the auxiliary storage unit 14 stores programs for implementing the three-dimensional information reconstruction unit 110 , the simulated SAR image generation unit 120 , and the second motion detection unit 140 .

[0171] The signal processing system 102 may be implemented with a circuit including hardware components such as an LSI that realizes the functions shown in FIG.

[0172] Furthermore, the signal processing systems 100 to 102 may be realized by hardware that does not include a computer function using an element such as a CPU. For example, some or all of the components may be implemented by a general-purpose circuit, a dedicated circuit, a processor, or a combination of these. These may be implemented by a single chip (for example, the above-mentioned LSI), or by multiple chips connected via a bus. Some or all of the components may be implemented by a combination of the above-mentioned circuits and programs.

[0173] Furthermore, some or all of the components of the signal processing systems 100 to 102 may be configured with one or more information processing devices each including a calculation unit and a storage unit.

[0174] When some or all of the components are realized by a plurality of information processing devices, circuits, etc., the plurality of information processing devices, circuits, etc. may be centrally or distributed. For example, the information processing devices, circuits, etc. may be realized as a client-server system, a cloud computing system, etc., in a form in which each is connected via a communication network.

[0175] Next, an overview of the present invention will be described. Fig. 17 is a block diagram showing an overview of a signal processing system according to the present invention. A signal processing system 20 according to the present invention includes a generating means 21 (e.g., a simulated SAR image generating unit 120) that generates a simulated SAR image, which is a complex image showing a steady state suitable for the imaging conditions of the SAR image to be analyzed, using three-dimensional information, which is data having information on reflection intensity and phase information at three-dimensional positions in a steady state reconstructed using observed SAR images captured by SAR, and the imaging conditions of the SAR image to be analyzed.

[0176] Such an arrangement allows the signal processing system to detect deviations from steady state based on phase information.

[0177] Furthermore, the signal processing system 20 may include a calculation means (for example, a three-dimensional information reconstruction unit 110) that calculates three-dimensional information using the observed SAR images.

[0178] Such a configuration allows the signal processing system to reconstruct three-dimensional information using observed SAR images.

[0179] The signal processing system 20 may also include a detection means (e.g., a first change detection unit 130) that detects a change that has occurred in an area in the SAR image to be analyzed by comparing the SAR image to be analyzed with a simulated SAR image.

[0180] Such an arrangement allows the signal processing system to detect changes from steady state using the complex correlation coefficient between SAR images.

[0181] The detection means may detect the change by calculating the degree of similarity between the SAR image to be analyzed and the simulated SAR image. The detection means may calculate the degree of similarity using phase information indicated by the SAR image to be analyzed and phase information indicated by the simulated SAR image. The degree of similarity may be a coherence value.

[0182] With such a configuration, the signal processing system can detect a change from the steady state using a coherence value determined from a pair of a SAR image to be analyzed and a simulated SAR image.

[0183] In addition, the generating means 21 may generate a simulated SAR image for each of the shooting conditions of the multiple SAR images to be analyzed, and the detecting means may calculate a degree of similarity across multiple pairs of the SAR image to be analyzed and the simulated SAR image, and detect a change using the calculated degrees of similarity.

[0184] With such a configuration, the signal processing system can detect a change from the steady state by using a plurality of complex correlation coefficients calculated from a plurality of pairs of the SAR image to be analyzed and the simulated SAR image.

[0185] Although the present invention has been described above with reference to the embodiment, the present invention is not limited to the above embodiment. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present invention within the scope of the present invention. [Explanation of symbols]

[0186] 11 CPU 12 Main memory 13. Communications Department 14 Auxiliary storage 15 Input section 16 Output section 17 System Bus 20, 100, 101, 102 Signal Processing System 21 Generation means 110 3D information reconstruction unit 120 Simulated SAR image generation unit 130 First change detection unit 140 Second change detection unit 200 SAR image storage unit

Claims

1. A generating means is provided for generating a simulated SAR image, which is a complex image showing the steady state suitable for the imaging conditions of the SAR image to be analyzed, by using three-dimensional information, which is data having information on reflection intensity and phase information at three-dimensional positions in a steady state reconstructed using an observation SAR image captured by a synthetic aperture radar (SAR), and the imaging conditions of the SAR image to be analyzed.

1. A signal processing system comprising:

2. A calculation means for calculating the three-dimensional information using the observed SAR image.

2. The signal processing system of claim 1.

3. and detecting means for detecting a change occurring in an area in the SAR image to be analyzed by comparing the SAR image to be analyzed with the simulated SAR image.

3. The signal processing system according to claim 1.

4. The detection means detects the change by calculating a degree of similarity between the SAR image to be analyzed and the simulated SAR image.

4. The signal processing system according to claim 3.

5. The detection means calculates the degree of similarity using phase information indicated by the SAR image to be analyzed and phase information indicated by the simulated SAR image.

5. The signal processing system according to claim 4.

6. The degree of similarity is the coherence value.

6. The signal processing system according to claim 5.

7. The generating means includes: generating the simulated SAR image for each of the imaging conditions of the plurality of SAR images to be analyzed; The detection means is calculating the degree of similarity across a plurality of pairs of the SAR image to be analyzed and the simulated SAR image; The change is detected using the calculated degrees of similarity. A signal processing system according to any one of claims 4 to 6.

8. A computer generates a simulated SAR image, which is a complex image showing the steady state suitable for the imaging conditions of the SAR image to be analyzed, by using three-dimensional information, which is data having information on reflection intensity and phase information at three-dimensional positions in a steady state reconstructed using observed SAR images taken by a synthetic aperture radar (SAR), and the imaging conditions of the SAR image to be analyzed. A signal processing method comprising:

9. A computer comprising: A simulated SAR image is generated, which is a complex image showing a steady state suitable for the imaging conditions of the SAR image to be analyzed, by using three-dimensional information, which is data having information on reflection intensity and phase information at a three-dimensional position in a steady state reconstructed using an observation SAR image captured by a synthetic aperture radar (SAR), and the imaging conditions of the SAR image to be analyzed. A signal processing program for

Images