System and method for SAR-based 3D deformation monitoring

Abstract

A system and method for synthetic aperture radar (SAR) based three-dimensional (3D) deformation measurement is provided herein. The synthetic aperture radar (SAR) system includes a SAR computer system for three dimensional (3D) deformation monitoring having a 3D acquisition planner module that receives any one or more of multi-sensor characteristic data, target requirements data, and ancillary datasets, to generate an observation plan, a data acquisition module that transmits the observation plan to trigger the acquisition of SAR data from at least one SAR satellite, and an integration processing module that computes 3D surface displacement measurements from the SAR data to measure 3D deformation.

Description

SYSTEM AND METHOD FOR SAR-BASED 3D DEFORMATION MONITORING Technical Field

[0001] The following relates generally to spaceborne remote sensing and monitoring, and more particularly to systems and methods for synthetic aperture radar based three-dimensional deformation monitoring.Introduction

[0002] A mid-inclination orbit for a satellite synthetic aperture radar (SAR) instrument has some disadvantages compared to near-polar orbiting SARs, including a lack of coverage at high latitudes (beyond + / - 62.5 degrees, for example). SAR mission design has conventionally been focused on global coverage to enhance the usability of the imagery. Recent systems have taken a new approach to enhance imaging capabilities at low to mid-latitudes at the expense of high latitudes. Additionally, spacecraft engineering for mid-inclination SAR platforms may be considerably more complex, including unique constraints on power, thermal sensitivity, eclipses, environmental conditions, and magnetic field variations. This requires redesign of heritage components / systems that makes developing a mid-inclination SAR platform more difficult than a near-polar SAR platform.

[0003] This trade-off that is being made by recent systems is somewhat enabled by extensive global SAR coverage at C- and X- band provided by recent space missions. SAR data can therefore be supplemented at high latitudes by various other platforms. The mid-inclination of recent systems may provide increased coverage and revisit at the mid-to-low latitudes where there may be commercial demand for imagery at the expense of lack of coverage at higher latitudes.

[0004] The benefit of interferometric SAR (InSAR) from a mid-inclined orbit has been previously described from a theoretical perspective in T. J. Wright, B. E. Parsons, and Z. Lu, “Toward mapping surface deformation in three dimensions using InSAR,” Geophysical Research Letters, vol. 31 , no. 1 , 2004 (Wright et al. 2004); however, this potential has not yet been realized or developed in detail.

[0005] Other systems may operate several satellites of X-band SAR constellation in mid-inclination orbits. However, the orbital tubes for these satellites are conventionally too large to support consistent InSAR and repeat imaging for change detection, nullifying their use for the purposes described herein. Another disadvantage of these other systems is the limited spatial coverage that they may provide.

[0006] Other solutions utilize the pixel offset method and multi-aperture interferometry to overcome this problem; but these methods have their own sensitivity limitations and may only be suitable for detecting large deformation. These limitations include low spatial resolution, vulnerability to temporal decorrelation and larger uncertainty in the north-south component compared to what a mid-inclination orbit could provide.

[0007] Accordingly, there is a need for an improved system and method for synthetic aperture radar based three-dimensional deformation monitoring that overcomes at least some of the disadvantages of existing systems and methods.Summary

[0008] Provided is a synthetic aperture radar (SAR) system comprising a SAR computer system for three-dimensional (3D) deformation monitoring comprising a 3D acquisition planner module that receives any one or more of multi-sensor characteristic data, target requirements data, and ancillary datasets, to generate an observation plan, a data acquisition module that transmits the observation plan to trigger the acquisition of SAR data from at least one SAR satellite, and an integration processing module that computes 3D surface displacement measurements from the SAR data to measure 3D deformation.

[0009] Provided is a method for synthetic aperture radar (SAR) based three-dimensional (3D) deformation monitoring. The method includes receiving any one or more of multi-sensor characteristic data, target requirements data, and ancillary datasets, to generate an observation plan, acquiring SAR data that was captured by at least one SAR satellite, and computing 3D surface displacement measurements from the SAR data to measure 3D deformation.

[0010] The at least one SAR satellite may include a first satellite in mid-inclination orbit.

[0011] The SAR data may include interferometric SAR (InSAR) data from at least three different viewing geometries. The integration processing module may combine at least three viewing geometries to measure 3D deformation.

[0012] The SAR data may include InSAR data from two different viewing geometries. The integration processing module may combine two viewing geometries and additional deformation constraints to measure 3D deformation.

[0013] The multi-sensor characteristics data may include any one or more of nominal orbits, look directions, beam modes, and tasking availabilities of satellite-based payloads.

[0014] The target requirements data may include any one or more of a model or estimate of the expected deformation, a time period, and a geographic location.

[0015] The ancillary datasets may include any one or more of land cover model data, digital elevation model (DEM) data, global historical climatology data, and weather station data.

[0016] The system may further include artificial radar reflectors for 3D deformation monitoring. The data acquisition module may receive SAR data from the artificial radar reflectors.

[0017] The data acquisition module may receive SAR data from customized artificial radar reflectors for broad azimuth sensitivity to radar pulses from both midinclination orbits and sun-synchronous orbits. Reflections from the artificial radar reflectors may be captured in the SAR data and received by the data acquisition module.

[0018] The SAR computer system may include a 3D decomposition module that produces 3D deformation time series data from the SAR data.

[0019] The SAR computer system may include a diurnal / seasonal deformation model fitting module. The diurnal / seasonal deformation model fitting module may extract diurnal and seasonal components of surface displacement related to thermal,atmospheric, and weather phenomena through non-integer day repeat imaging from a SAR in a mid-inclination orbit.

[0020] The SAR computer system may include a phase bias mitigation module. The phase bias mitigation module may mitigate the phase bias introduced by acquisition time phasing for repeat SAR imaging from mid-inclination orbits.

[0021] The method may further include deploying artificial radar reflectors for 3D deformation monitoring.

[0022] The method may further include performing 3D decomposition to produce 3D deformation time series data from the SAR data.

[0023] The method may further include extracting diurnal and seasonal components of surface displacement related to thermal, atmospheric, and weather phenomena through non-integer day repeat imaging from a SAR in a mid-inclination orbit.

[0024] The method may further include mitigating the phase bias introduced by acquisition time phasing for repeat SAR imaging from mid-inclination orbits.

[0025] Other aspects and features will become apparent, to those ordinarily skilled in the art, upon review of the following description of some exemplary embodiments.Brief Description of the Drawings

[0026] The drawings included herewith are for illustrating various examples of articles, methods, and apparatuses of the present specification. In the drawings:

[0027] Figure 1 is a diagram of a system for synthetic aperture radar based three-dimensional deformation, according to an embodiment;

[0028] Figure 2 is a block diagram of a computer system for synthetic aperture radar, according to an embodiment;

[0029] Figure 3 is a block diagram of a computer system for synthetic aperture radar based three-dimensional deformation, according to an embodiment;

[0030] Figure 4 is a flowchart of a method for synthetic aperture radar based three-dimensional deformation, according to an embodiment; and

[0031] Figure 5 is a flowchart of an example method for synthetic aperture radar based three-dimensional deformation, according to an exemplary embodiment.Detailed Description

[0032] Various apparatuses or processes will be described below to provide an example of each claimed embodiment. No embodiment described below limits any claimed embodiment and any claimed embodiment may cover processes or apparatuses that differ from those described below. The claimed embodiments are not limited to apparatuses or processes having all of the features of any one apparatus or process described below or to features common to multiple or all of the apparatuses described below.

[0033] One or more systems described herein may be implemented in computer programs executing on programmable computers, each comprising at least one processor, a data storage system (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. For example, and without limitation, the programmable computer may be a programmable logic unit, a mainframe computer, server, and personal computer, cloud-based program or system, laptop, personal data assistance, cellular telephone, smartphone, or tablet device.

[0034] Each program may be implemented in a high-level procedural or object-oriented programming and / or scripting language to communicate with a computer system. However, the programs can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language. Each such computer program is preferably stored on a storage media or a device readable by a general or special purpose programmable computer for configuring and operating the computer when the storage media or device is read by the computer to perform the procedures described herein.

[0035] A description of an embodiment with several components in communication with each other does not imply that all such components are required. On the contrary, a variety of optional components are described to illustrate the wide variety of possible embodiments of the present invention.

[0036] Further, although process steps, method steps, algorithms or the like may be described (in the disclosure and I or in the claims) in a sequential order, such processes, methods and algorithms may be configured to work in alternate orders. In other words, any sequence or order of steps that may be described does not necessarily indicate a requirement that the steps be performed in that order. The steps of processes described herein may be performed in any order that is practical. Further, some steps may be performed simultaneously.

[0037] When a single device or article is described herein, it will be readily apparent that more than one device I article (whether or not they cooperate) may be used in place of a single device I article. Similarly, where more than one device or article is described herein (whether or not they cooperate), it will be readily apparent that a single device I article may be used in place of the more than one device or article.

[0038] Referring now to Figure 1, shown therein is system 100 for synthetic aperture radar (SAR) based three-dimensional (3D) deformation monitoring, according to an embodiment. The system 100 may support unique SAR analytics enabled by a SAR constellation. In particular, the system 100 may support interferometric SAR (InSAR) applications for any one or more of military intelligence, monitoring of critical infrastructure, environmental monitoring, and disaster response. The system 100 may provide diverse viewing geometries for interferometric surface displacement measurements to allow the full 3D surface displacement vector to be determined.

[0039] The system 100 may include a set of tools, algorithms and operations to enable inversion of full 3D surface displacement vectors from spaceborne SAR. The set of tools may include any one or more of selecting SAR acquisition geometries, optimizing number and placement of artificial radar reflectors to boost 3D deformation accuracies, and processing data from multiple SAR sensors and / or geometries to 3D deformation time series.

[0040] The system 100 includes a plurality of satellites: a first satellite 102a, a second satellite 102b, and a third satellite 102c. Each of the satellites 102a, 102b, 102c include at least one SAR sensor for collecting SAR data. While three satellites 102a, 102b, 102c are shown in Figure 1 , other numbers of satellites may be used.

[0041] The satellites 102a, 102b, 102c travel along an orbit around the Earth. The satellites 102a, 102b, and 102c may have different orbits and / or ground tracks from each other. The orbit may be a sun synchronous orbit (SSO) or a mid-inclination orbit. The satellites 102a, 102b, and 102c each have an orbit that is controlled, within a tube, to provide repeat imaging of a scene with the same geometry after a set time (the repeat cycle). The first satellite 102a may be a C-band satellite, and the second satellite 102b may be a trailing X-band satellite, having a shared ground track.

[0042] When performing 3D deformation monitoring, the system 100 plans for acquisition of, tasks, collects, and uses / processes InSAR data including InSAR image stacks.

[0043] The system 100 obtains InSAR image stacks from at least three different viewing geometries. The InSAR image stacks may be provided by three different satellites 102a, 102b, 102c. The satellites 102a, 102b, 102c may all be in SSO. The satellites 102a, 102b, 102c may all be in mid inclination orbit. The satellites 102a, 102b, 102c may include at least one SSO satellite and at least one mid inclination satellite (e.g., two SSO, one mid inclination; one SSO, two mid inclination). A single mid-inclination satellite may supply all three InSAR image stacks from one or more beam modes and various orbit or look directions. These inputs may be separate satellites or could come from the same satellite. The InSAR image stacks could be supplied by three separate satellites.

[0044] The system 100 may have at least one satellite in mid inclination orbit.

[0045] The system 100 may have satellites in SSO, for example in polar regions where satellites having mid-inclination orbits are not available.

[0046] The system 100 may include one satellite (e.g., satellite 102a) having three different viewing geometries that are used to perform 3D deformation monitoring.

[0047] The system 100 may include at least three different viewing geometries provided by at least two different satellites (e.g., satellite 102a, satellite 102b). The time series of 3D deformation measurements includes processing 3 stacks of images. Each stack represents a collection of SAR imagery suitable for interferometric processing.

[0048] The 3D deformation measurements may be derived from three different viewing geometries and two different satellites. Stack 1, stack 2, and stack 3 may represent the collection of SAR images obtained by satellites 102a and 102b from Figure 1.

[0049] In a particular example, stack 1 is ascending, left-look, mid-inclination, stack 2 is descending, right-look, mid-inclination, and stack 3 is ascending, right-look, SSO. Ascending and descending refer to ascending and descending orbit directions. Left-look and right-look refer to the look direction of the SAR. Mid-inclination and SSO (sun-synchronous orbit) refer to the type of orbit for each satellite. In this case, “stack 1” and “stack 2” can be obtained from the same SAR satellite (in a mid-inclination orbit) using the same beam mode but with differing orbit and look directions.

[0050] The satellite 102a collects SAR data about a target 104. The satellite 102a may collect SAR data in land environments on the Earth.

[0051] The system 100 includes a ground terminal 106 for receiving the captured SAR data from the satellite 102a. The ground terminal 106 may include a receiver and a computer system for processing received SAR data (e.g., raw SAR data). In some cases, the ground terminal 106 may process raw SAR data into a format suitable for ingestion or use by a computer system.

[0052] The system 100 includes a server system 108 for performing operations on the SAR data. The server 108 receives SAR data from the ground terminal 106. The server system 108 communicates with the ground terminal 106 via a communication network 110. The network 110 may be a wide area network, such as the Internet. Communication may include sending and receiving data.

[0053] The server 108 may receive the SAR data from a source or device other than the ground terminal 106. For example, in an embodiment, the server 108 may receive the SAR data from another computer or data storage device.

[0054] The system 100 includes a user device 112 for operation by a user. The server 108 communicates with the user device 112 via network 110. The user device 112 communicates with the server system 108 over the network 110. While a single servercomputer 108 and a single user device 112 are shown in Figure 1, the number of servers 108 and user devices 112 may vary (e.g., multiple) and the number is not particularly limited.

[0055] The server 108 includes a SAR computer system 120 that performs synthetic aperture radar based three-dimensional deformation analysis. The user device 112 includes a user interface of the SAR computer system 120.

[0056] The SAR computer system 120 may be hosted by the server system 108, installed locally on the user device 112, or run on both the server system 108 and the user device 112. The SAR computer system 102 may be hosted in a cloud server.

[0057] The user device 112 is configured to receive input from a user and display data generated by the server system 108. The input data received from a user may be used to request certain data generated and stored by the server system 108. The user device 112 is configured to display a graphical user interface that allows a user to interact with the server 108. The user interface may include a series of user interface screens for receiving user input and displaying output data generated by the server system 108.

[0058] The system 100 also includes ancillary data source 114. The server 108 (or user device 112) communicates with the ancillary data source 114 via the network 110. The ancillary data source 114 stores one or more types of ancillary data that is used by the SAR computer system 120. While a single data source 114 is shown in Figure 1, there may be multiple ancillary data sources 114. Generally, the SAR computer system 120 may be configured to request data from the ancillary data source 114. The ancillary data 114 source may be one or more databases.

[0059] The system 100 may include mid-inclination orbital SAR satellites 102a, 102b, 102c that supports consistent interferometric imaging capabilities at high resolution and wide coverage at C-band. While conventional systems may include mid-inclination orbiting SAR satellites as part of an X-band constellation, these satellites may not have the capability to maintain an orbital tube that is narrow enough for consistent InSAR applications. The system 100 may provide high resolution wide coverage C-band midinclination SAR imaging. The system 100 may be beneficial in conditions wheremovement is characterized by fast-moving wide area deformation, such as earthquakes. The system 100 may be applied to X-band data.

[0060] Conventional InSAR techniques may only measure one-dimensional motion along a single radar line-of-sight (LOS). To retrieve the three components of deformation, the system 100 includes at least three non-coplanar LOS vectors with sufficient angular diversity. This may be achieved by utilizing multiple InSAR stacks acquired from a combination of different orbits, pass directions, incidence angles, and left and right looking observations.

[0061] Conventional operational spaceborne SAR sensors acquire images from sun-synchronous orbits, mostly using right-looking modes. The InSAR measurements derived from these geometrical configurations provide accurate vertical and east-west deformation measurements, however the north-south component remains poorly resolved. The mid-inclination orbit of the system 100 may introduce viewing geometries with improved sensitivity to north-south oriented horizontal displacement.

[0062] The mid-inclination orbit for the system 100 results in a change in the local time for repeat orbit imaging of the same target from the same SAR configuration (beam mode, look direction, etc.). Being sun-synchronous, conventional near-polar orbiting SAR satellites will image targets at the same time of day for repeat imagery (integer numbers of days for repeat cycle). Since the system 100 may image areas at slightly different times of day for repeat acquisitions, changing from one acquisition to the next, this introduces new temporal information on the scattering characteristics of imaged targets. The system 100 utilizes this information to derive additional insights on target properties and changes from short to long time scales.

[0063] While conventional SAR constellations do not offer multi-band imaging opportunities, the system 100 may enable imaging at both C- and X-band. If satellite 102b shares the same ground-track as satellite 102a, and if satellite 102b acquires data at X-band and satellite 102a acquires data at C-band, this introduces opportunities for rapid multi-band repeat imaging that could be exploited for surface change detection. Consideration of these capabilities in a 3D geometry may enable further analytics for 3D surface deformation and change.

[0064] The system 100 captures improvements in analytic techniques that are enabled by new technology. The improvements include 3D decomposition. 3D decomposition is a natural extension of 2D decomposition routinely performed using observations from near-polar orbiting SARs. With 3D, the decomposition problem is more determined.

[0065] Further, 2D decomposition from current SAR platforms is limited by tasking availability and limited viewing geometries currently available. The increased diversity in available viewing geometries introduced by the system 100 for both 2D and 3D decomposition provides opportunities (e.g., using an acquisition planning tool) to identify optimal beam combinations in this expanded parameter space.

[0066] While conventional techniques may mitigate atmospheric (weather) and thermal (diurnal and seasonal) effects in InSAR deformation measurements, extending these techniques with the unique temporal sampling of the system 100 (non-integer day repeat cycle) may provide improvements.

[0067] While corner reflectors, and other artificial radar reflectors such as e-transponders, may be installed for visibility from several acquisition geometries, these are typically only oriented for ascending / descending orbits of near-polar orbiting SARs. The system 100 includes visibility from a variety of geometries.

[0068] Referring now to Figure 2, shown therein is a SAR computer system 200, in accordance with an embodiment. The SAR computer system 200 may be the SAR computer system 120 of Figure 1.

[0069] The SAR computer system 200 includes a software application that receives and stores SAR data. The system 200 includes several tools and modules to inform the tasking of a SAR satellite system (e.g., system 100), to enable any one or more of analytics, to reduce phase noise in InSAR measurements, and to carry out processing to derive analysis-ready products.

[0070] The SAR computer system 200 includes multi-sensor characteristics data 202. The multi-sensor characteristics data 202 may include any one or more of nominalorbits, look directions, beam modes, and tasking availabilities of satellite-based InSAR payloads.

[0071] The SAR computer system 200 includes target requirements data 204. The target requirements data 204 may include any one or more of a model or estimate of the expected deformation, a time period, and a geographic location. Target requirements may be defined by the user. The user may provide the target requirements data 204 as input through a graphical user interface of the SAR computer system 200.

[0072] The SAR computer system 200 includes ancillary datasets 206. The ancillary datasets 206 may include any one or more of land cover model data, digital elevation model (DEM) data, global historical climatology data, and weather station data. The ancillary datasets 206 may be received by the SAR computer system 200 from an ancillary data source (e.g., ancillary data source 114).

[0073] The SAR computer system 200 includes a 3D acquisition planner module 208. The 3D acquisition planner model receives any one or more of multi-sensor characteristic data 202, target requirements data 204, and ancillary datasets 206. The 3D acquisition planner module 208 plans the acquisition of three or more InSAR stacks. Each InSAR stack includes data acquired in a fixed imaging geometry. Each InSAR stack measures the deformation along its respective line-of-sight. 3D deformation monitoring is possible using three or more diverse lines-of-sight. Diverse lines-of-sight are possible by using a combination of SAR data acquired in mid-inclination and sun-synchronous orbits.

[0074] The 3D acquisition planner module 208 generates an observation plan 210. The 3D acquisition planner module 208 supports three dimensional (3D) InSAR from SAR sensors in mid-inclination orbits combined with sun-synchronous orbits.

[0075] The 3D acquisition planner module 208 may include a set of tools, algorithms, and operations to optimally plan a sequence of spaceborne SAR image acquisitions to enable 3D deformation time series monitoring. The 3D acquisition planner module 208 may consider different capabilities and orbits of various SAR satellites and the unique combinations resulting from their temporal, spectral, and spatial overlaps. The 3D acquisition planner module 208 may generate high fidelity simulations of the quality of the derived 3D deformation using supporting datasets to improve planning optimization.

[0076] The system 200 may include an InSAR processing module for inverting 3D deformation. The InSAR processing module may include a set of methods to produce high quality 3D deformation time series data from a collection of multi-sensor SAR imagery. The InSAR processing module may provide flexibility to accommodate different deformation characteristics (i.e. fast / slow, linear / non-linear). The InSAR processing module may include automated optimization of parameters to produce high quality results given an observation scenario.

[0077] The SAR computer system 200 includes a data acquisition module 212. The 3D acquisition planner module 208 outputs the observation plan 210 to the data acquisition module 212.

[0078] The data acquisition module 212 transmits the observation plan to trigger the acquisition of SAR data from SAR satellites. The data acquisition module 212 may initiate the actioning of the observation plan by a system of satellites. The actioning of the observation plan may include tasking SAR sensors and the gathering of SAR image data. The satellite systems acquire the data. The data acquisition module 212 may fetch archived SAR data.

[0079] The data acquisition module 212 may receive SAR data from artificial radar reflectors. The data acquisition module 212 may acquire data obtained from customized artificial radar reflectors for broad azimuth sensitivity to radar pulses from both midinclination orbits and sun-synchronous orbits. Reflections from the artificial radar reflectors are captured in the SAR data and received by the data acquisition module 212. The data acquisition module 212 triggers the capture of SAR data 216 by SAR satellites. The SAR data may include payload records of received radar reflections that include reflections from the artificial radar reflectors.

[0080] The 3D Acquisition planner module 208 may provide a plan for the optimized deployment of artificial radar reflectors for 3D deformation monitoring from midinclination and SSO orbits. The artificial radar reflectors for 3D deformation monitoring may include mechanical design of artificial radar reflectors for multi-orbit visibility. The 3D acquisition planner module 208 may include methods for optimized number, placement, and orientation of artificial radar reflectors to improve deformation accuracy. The 3Dacquisition planner module 208 may consider land cover type and any existing conventional corner reflectors.

[0081] The SAR computer system 200 includes an integration processing module 218. The integration processing module 218 receives the SAR data 216. The 3D surface measurements are computed by the 3D decomposition module 224. The integration processing module 218 may perform interferometric processing up to the point of 3D decomposition, including any pre-processing for 3D decomposition. The integration processing module 218 computes 3D surface displacement measurements from multiband and multi-sensor combinations of InSAR measurements with at least one dataset resulting from a SAR in a mid-inclination orbit.

[0082] The integration processing module 218 may include methods to mutually process and combine multi-sensor SAR imagery suitable for interferometric processing. The integration processing module 218 may include consideration of variable metadata formatting, data types, and inter-sensor co-registration. The integration processing module 218 may include tools to convert data into compatible imagery as well as to exploit additional analytics enabled by broad spectral coverage (e.g., phase unwrapping).

[0083] The integration processing module 218 combines the viewing geometries to measure 3D deformation. The integration processing module 218 may combine at least three viewing geometries to measure 3D deformation. The integration processing module 218 may integrate SAR data from multiple sensors. The SAR data may include multisensor data at a single SAR frequency band. The integration processing module 218 may integrate SAR data across multiple bands. At high latitudes, the SAR data may not include mid-inclination orbit data.

[0084] The SAR data may include InSAR data from two different viewing geometries. The integration processing module 218 combines two viewing geometries and additional deformation constraints to measure 3D deformation. The additional deformation constraints may include constrained movement to a 2D plane or slope.

[0085] The SAR computer system 200 includes a 3D decomposition module 224 that produces 3D deformation time series data from the SAR data. The 3D decomposition module 224 extends 2D decomposition techniques with the SAR data to provide a moreaccurate 3D deformation result. The 3D decomposition module 224 includes a process to produce high quality 3D deformation time series data from a collection of multi-sensor SAR imagery.

[0086] The SAR computer system 200 includes a diurnal / seasonal deformation model fitting module 226. The diurnal / seasonal deformation model fitting module 226 extracts diurnal and seasonal components of surface displacement. The surface displacement may be related to thermal, atmospheric, and weather phenomena through non-integer day repeat imaging from a SAR in a mid-inclination orbit. The diurnal / seasonal deformation model fitting 226 uses data from at least one satellite that is in mid inclination orbit.

[0087] The diurnal / seasonal deformation model fitting module 226 includes method for extracting diurnal I seasonal surface displacement components through repeat cycle with non-integer number of days. The diurnal / seasonal deformation model fitting module 226 includes methods that incorporate ancillary datasets to fit models of diurnal and seasonal deformation trends from interferometric deformation time series modeling. The diurnal / seasonal deformation model fitting module 226 may include tools to interpret the models in terms of changing target properties. The diurnal / seasonal deformation model fitting module 226 may include tools to remove the models from deformation time series.

[0088] The SAR computer system 200 includes a phase bias mitigation module 228. The phase bias mitigation module 228 mitigates the phase bias. There may be phase bias present in InSAR deformation from SSO orbits (integer repeat cycles). The non-integer repeat cycles for mid-inclination orbiting SARs may provide insight into modeling and removing this phase bias. There may be additional sources of phase bias introduced by the non-integer repeat cycles.

[0089] The phase bias mitigation module 228 includes methods or mitigation of InSAR phase bias due to image acquisition at varying local time-of-day. The phase bias mitigation module 228 may reduce phase bias from deformation time series by better isolating variable target properties impacted by changing environmental conditions at different local times of day. The phase bias mitigation module 228 may include tools torelate the identified phase bias signal to ancillary datasets. The phase bias mitigation module 228 includes tools to remove the identified phase bias signal from deformation time series.

[0090] The SAR system 200 generates 3D deformation time series data 230.

[0091] The 3D deformation time series data 230 may be displayed to a user in a GUI for review by a user. The 3D deformation time series data 230 may be provided to another software application for further processing (e.g., as one input to third party software). The 3D deformation time series data 230 may be provided as input to a trained machine learning model configured to perform change detection.

[0092] The 3D deformation time series data may be used in a deformation monitoring application. For example, the 3D deformation time series data may be used to generate risk maps to help assess risk and / or determine risk.

[0093] The 3D deformation time series data may include time series data that is formatted as a series of images. The series of images are not the images as directly acquired by the satellites. The set of satellite line-of-sight acquired images may be processed to create a set of time series images, wherein each pixel value represents the east-west, north-south, or vertical deformation at that date. The system measures how the pixel value changes to determine insights from deformation overtime. While 2D has two components of deformation (for vertical and east-west horizontal motion), the 3D deformation time series data also includes north-south deformation.

[0094] The use of SAR sensors in different orbits and acquiring data in different look / pass / incidence angle directions may provide diverse viewing geometries for interferometric surface displacement measurements to allow the full 3D surface displacement vector to be precisely determined. Further, the SAR computer system 200 may increase the quality of the measurements by planning optimal beam mode configurations, reducing phase noise in observations using time series from novel artificial radar reflectors, and using state-of-the art algorithms for data processing.

[0095] In addition to 3D deformation monitoring measurements, the SAR computer system 200 may exploit the unique temporal sampling of repeat SAR images by thesatellite system to derive further analytics related to the temporal characteristics of the observed surface displacement. Multi-band InSAR measurements may provide additional confidence in resolving phase ambiguities in the surface displacement monitoring.

[0096] The availability of multiple polarizations may offer benefits in the development of solutions for exploitation of SAR information for different applications such as forestry, biomass, agriculture and wetland monitoring. Multiple polarizations may also lead to more robust 3D deformation inversion results.

[0097] Referring now to Figure 3, shown therein is a computer system 300 for SAR-based 3D deformation monitoring, according to an embodiment.

[0098] The computer system 300 may be implemented using the server system 108 and the user device 112 of Figure 1. The computer system 300 may be the SAR computer system 200 of Figure 2. The system 300 may be configured to implement any one or more of the methods described herein or portions thereof. The system 300 includes a memory 302 and a processor 304 in communication with the memory 302.

[0099] The processor 304 is configured to execute various software modules and components. In some embodiments, modules or components executed by the processor 304 may include server-side software components and client-side software components that communicate with each other in order to provide various features and functionalities of the system 300. In some cases, server-side components may be executed at a server computer and client-side components may be executed at a user device.

[0100] The system 300 includes a communication interface device 306 for transmitting and receiving data to and from other computing devices. The communication interface device 306 may include a network interface device for transmitting and receiving data via a network connection (e.g., local area network, wide area network, etc.). The network connection may be wired or wireless connection.

[0101] The system 306 includes a display device 308 for displaying data generated by the system 300. The display device 308 may be located at a user device, such as at user device 112 of Figure 1.

[0102] The system 300 includes an input device 310 for receiving input data from a user interacting with the system 300. For example, a user may use input device 310 to interact with the system 300 through a graphical user interface generated by the processor 304 and displayed via the display device 308. The input device 310 may be located at the user device, such as at operator station 108 of Figure 1. A user input may include, for example, initial conditions for planning a task or a command to uplink an approved task.

[0103] The processor 304 executes a SAR-based 3D deformation monitoring software application 312. The SAR computer system 120 of Figure 1 may include the SAR-based 3D deformation monitoring application 312.

[0104] The SAR-based 3D deformation monitoring application 312 includes a 3D acquisition planner module 314.

[0105] The SAR-based 3D deformation monitoring application 312 includes an integration processing module 318.

[0106] The SAR-based 3D deformation monitoring application 312 includes a 3D decomposition module 322.

[0107] The SAR-based 3D deformation monitoring application 312 includes a diurnal / seasonal deformation model fitting module 324.

[0108] The SAR-based 3D deformation monitoring application 312 includes a phase bias mitigation module 326.

[0109] The SAR-based 3D deformation monitoring application 312 includes a graphical user interface (GUI) module 328.

[0110] The memory 302 includes multi-sensory characteristics data 330. The multisensor characteristics data 330 includes any one or more of nominal orbits data 332, look directions data 334, beam modes data 336, and tasking availabilities data 338.

[0111] The memory 302 includes target requirements data 340. The target requirements data 340 includes any one or more of time period data 342, and geographic location data 344, and a model or estimate of the expected deformation 345.

[0112] The memory 302 includes ancillary datasets 346. The ancillary datasets 346 includes any one or more of land cover data 348, digital elevation model (DEM) data 350, and global climate model (GCM) I weather station data 352. The memory 302 may include artificial reflector data 358 that includes the received signal from the artificial reflectors. The memory 302 may include algorithms for optimizing artificial radar reflector placement / orientation.

[0113] The memory 302 includes observation plan data 354. The memory 302 includes SAR data 356. The memory 302 includes 3D deformation time series data 360.

[0114] Referring now to Figure 4, shown therein is a method 400 for SAR-based 3D deformation monitoring, according to an embodiment.

[0115] At 402, operational data is received. The operational data includes any one or more of multi-sensor characteristics, target requirements, and ancillary datasets.

[0116] At 404, an observation plan is generated from the operational data using a 3D acquisition planner module.

[0117] At 406, SAR data is acquired that was captured by at least one SAR satellite. Artificial radar reflectors for 3D deformation monitoring may be used.

[0118] At 408, interferometric processing is performed by applying interferometric and pre-processing up to the point of 3D decomposition.

[0119] At 410, 3D decomposition is performed to produce 3D deformation time series data from the SAR data.

[0120] At 412, optionally diurnal I seasonal deformation model fitting is performed.412 may include extracting diurnal and seasonal components of surface displacement related to thermal, atmospheric, and weather phenomena through non-integer day repeat imaging from a SAR in a mid-inclination orbit.

[0121] At 414, optionally phase bias is mitigated. 414 may include mitigating the phase bias introduced by acquisition time phasing for repeat SAR imaging from midinclination orbits.

[0122] At 416, the resulting 3D deformation time series data is stored.

[0123] Referring now to Figure 5, shown therein is an example method 500 for 3D deformation monitoring, in accordance with an exemplary embodiment.

[0124] The example method 500 aims to quantify ground uplift from aquifer rebound due to inactivity of underground mines over a wide region in a particular geography. Horizontal ground motions in east-west and north-south planes are used to understand the extent of the deformation. The area may have been monitored for several years to understand evolution of the ground movement during the decommissioning phase of the mines.

[0125] The 3D deformation time series method 500 may be used to inform geotechnical modeling, operations during the decommissioning phase, and regulatory reporting to relevant government and environmental agencies.

[0126] At 502, the target area and time period are identified from the user.

[0127] At 504, the suitability of InSAR is evaluated to determine if InSAR will meet the user’s objectives. The user provides details on the expected deformation. For example, slow, predominantly linear deformation with centralized uplift and radially extending horizontal motion to several kilometers may be well suited to be captured by InSAR monitoring.

[0128] At 506, potential SAR sensors are identified to incorporate in the monitoring plan. A satellite in mid-inclination orbit may provide angular diversity for 3D decomposition. Access to sensor details and tasking information is provided in preparation of 3D acquisition planning.

[0129] At 508, ancillary datasets are compiled from customer and external sources. The ancillary datasets may include any one or more of digital elevation model (DEM), land cover, global climate model (GCM) and weather station data. High resolution DEM or weather station data may be available from the user. Land cover map data from one of several open archives may be downloaded.

[0130] At 510, a 3D acquisition planner (e.g., 3D acquisition planner module 208) identifies suitable image geometry stacks. The optimum observation plan is determined, optionally in consultation with the user.

[0131] For this example, one near-polar SSO beam mode and two mid-inclination satellite beam modes are selected.

[0132] At 512, it is determined if artificial radar reflectors are needed, and if so, how many and where to deploy in the geographic location. Simulations from the 3D acquisition planner may be leveraged to assess use of artificial radar reflectors. If appropriate, the installation plan is optimized for any one or more of expected deformation model, site characteristics, and user budget. If appropriate, the artificial radar reflectors are manufactured and installed.

[0133] At 514, the sensors are tasked and SAR data is acquired according to the observation plan. In this example, tasking requests are submitted for the two midinclination orbiting satellite beam modes according to the observation plan and imagery as collected is compiled. In this example, the near-polar SSO imagery is downloaded as it is obtained from the relevant archives according to the observation plan (some missions may have a predetermined acquisition plan and may not have specific tasking).

[0134] At 516, interferometric processing of multi-sensor (potentially multi-band for other examples) SAR data is performed. SAR data acquired from each sensor may be processed leveraging ancillary data individually from complex data (e.g., single-look complex (SLC) data) to a predetermined, consistent processed level. Interferometric processing may be applied to each image stack separately to measure deformation along each 1D line-of-sight.

[0135] At 518, 3D decomposition of the combined multi-sensor dataset is performed.

[0136] At 520, a diurnal / seasonal deformation model is fit to the 3D decomposition result. For this specific example, diurnal / seasonal deformation trends are removed from the 3D decomposition result to isolate the long-term trends related to the ongoing rebound processes.

[0137] At 522, a phase bias model is fit to the 3D decomposition result, leveraging ancillary data and the diurnal / seasonal deformation model. For this specific example, themodelled phase bias from the 3D decomposition result is removed to isolate the longterm trends related to the ongoing rebound processes.

[0138] At 524, the final 3D decomposition result is saved as a 3D deformation time series of raster images or vector geospatial data files. The 3D deformation time series data is uploaded to a data visualization portal for the user to interact with and download data. A report may be delivered to the user describing any one or more of data collection, a high-level overview of processing applied, and key features of the derived 3D deformation time series to aid interpretation.

[0139] While the above description provides examples of one or more apparatus, methods, or systems, it will be appreciated that other apparatus, methods, or systems may be within the scope of the claims as interpreted by one of skill in the art.

Claims

Claims:

1. A synthetic aperture radar (SAR) system comprising:a SAR computer system for three dimensional (3D) deformation monitoring comprising:a 3D acquisition planner module that receives any one or more of multisensor characteristic data, target requirements data, and ancillary datasets, to generate an observation plan;a data acquisition module that transmits the observation plan to trigger the acquisition of SAR data from at least one SAR satellite; andan integration processing module that computes 3D surface displacement measurements from the SAR data to measure 3D deformation.

2. The system of claim 1 , wherein the at least one SAR satellite includes a first satellite in mid-inclination orbit.

3. The system of claim 1 , wherein the SAR data includes interferometric SAR (InSAR) data from at least three different viewing geometries, and wherein the integration processing module combines at least three viewing geometries to measure 3D deformation.

4. The system of claim 1, wherein the SAR data includes InSAR data from two different viewing geometries, and wherein the integration processing module combines two viewing geometries and additional deformation constraints to measure 3D deformation.

5. The system of claim 1 , wherein the multi-sensor characteristics data includes any one or more of nominal orbits, look directions, beam modes, and tasking availabilities of satellite-based payloads.

6. The system of claim 1 , wherein the target requirements data includes any one or more of a model or estimate of the expected deformation, a time period, and a geographic location.

7. The system of claim 1 , wherein the ancillary datasets include any one or more of land cover model data, digital elevation model (DEM) data, global historical climatology data, and weather station data.

8. The system of claim 1 further comprising artificial radar reflectors for 3D deformation monitoring, and wherein the data acquisition module receives SAR data from the artificial radar reflectors.

9. The system of claim 8, wherein the data acquisition module receives SAR data from customized artificial radar reflectors for broad azimuth sensitivity to radar pulses from both mid-inclination orbits and sun-synchronous orbits, and wherein reflections from the artificial radar reflectors are captured in the SAR data and received by the data acquisition module.

10. The system of claim 1, wherein the SAR computer system includes a 3D decomposition module that produces 3D deformation time series data from the SAR data.

11. The system of claim 1, wherein the SAR computer system includes a diurnal / seasonal deformation model fitting module, wherein the diurnal / seasonal deformation model fitting module extracts diurnal and seasonal components of surface displacement related to thermal, atmospheric, and weather phenomena through non-integer day repeat imaging from a SAR in a mid-inclination orbit.

12. The system of claim 1, wherein the SAR computer system includes a phase bias mitigation module, wherein the phase bias mitigation module mitigates the phase bias introduced by acquisition time phasing for repeat SAR imaging from midinclination orbits.

13. A method for synthetic aperture radar (SAR) based three-dimensional (3D) deformation monitoring, the method comprising:receiving any one or more of multi-sensor characteristic data, target requirements data, and ancillary datasets, to generate an observation plan;acquiring SAR data that was captured by at least one SAR satellite; andcomputing 3D surface displacement measurements from the SAR data to measure 3D deformation.

14. The method of claim 13, wherein the at least one SAR satellite includes a first satellite in mid-inclination orbit.

15. The method of claim 13, wherein the SAR data includes interferometric SAR (InSAR) data from at least three different viewing geometries, and wherein the method further includes combining the at least three viewing geometries to measure 3D deformation.

16. The method of claim 13, wherein the SAR data includes InSAR data from two different viewing geometries, and wherein the method further includes combining two viewing geometries and additional deformation constraints to measure 3D deformation.

17. The method of claim 13, wherein the multi-sensor characteristics data includes any one or more of nominal orbits, look directions, beam modes, and tasking availabilities of satellite-based payloads.

18. The method of claim 13, wherein the target requirements data includes any one or more of a model or estimate of the expected deformation, a time period, and a geographic location.

19. The method of claim 13, wherein the ancillary datasets include any one or more of a land cover model data, a digital elevation model (DEM) data, global historical climatology data, and weather station data.

20. The method of claim 13 further comprising deploying artificial radar reflectors for 3D deformation monitoring.

21. The method of claim 13 further comprising performing 3D decomposition to produce 3D deformation time series data from the SAR data.

22. The method of claim 13 further comprising extracting diurnal and seasonal components of surface displacement related to thermal, atmospheric, and weather phenomena through non-integer day repeat imaging from a SAR in a midinclination orbit.

23. The method of claim 13 further comprising mitigating the phase bias introduced by acquisition time phasing for repeat SAR imaging from mid-inclination orbits.

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