Systems and methods for sensing planetary topology

Abstract

A sensor system for sensing a topography of a planet is disclosed herein. The system includes at least one on-board processor. The system further includes at least one first and second sensor configured on a vehicle moving with an altitude from a crustal portion of the planet to sense the topography of a sample area of ​​the planet. The sensor is communicatively coupled to the on-board processor. The system includes a memory communicatively coupled to the on-board processor, the memory storing executable instructions that, when executed by the processor, cause the processor to facilitate synchronized and aligned orientation of the sensor toward the sample area to sense a spatially and temporally aligned data set. The processor then receives and processes the spatially and temporally aligned data set to perform pixel-level coregistration of the spatially and temporally aligned data set.

Description

[BRIEF DESCRIPTION OF THE DRAWINGS]

[0001] [MODE FOR CARRYING OUT THE INVENTION]

[0002]

[0001] As mentioned in the preceding section of this document, currently the raw data acquired by optical sensors and microwave sensors come from separate sources, each having respective technical specifications and parameters. Furthermore, considering how differently both sensors operate, co-registration of these data sets when obtained from different separate sources is a difficult challenge and leads to many errors. As a result, the overall process currently consumes a large amount of time and labor, and is still limited in terms of the accuracy obtained as a result of data fusion.

[0003]

[0002] In order to overcome the aforementioned problems, the present invention contemplates a sensor system for sensing planetary topology, which involves the use of two different sensors including optical sensing, infrared sensing, and microwave sensing that are synchronized and aligned, and configured to operate simultaneously. Furthermore, the three sensors are configured for sensing a sample area of topology so as to capture spatially and temporally aligned data sets associated with characteristics of the sample area.

[0004]

[0003] Figure 1A shows a block diagram illustrating the operating principle of a sensor system 100 (hereinafter referred to as System 100) for sensing the topology of a planet, according to one embodiment of the present invention. System 100 includes at least one onboard processor 102 and a memory 104 communicatively coupled to at least one onboard processor, the memory storing executable instructions for the operation of System 100. System 100 further includes at least one first sensor 106 and at least one second sensor 108. The first sensor 106 and the second sensor 108 are communicatively coupled to the onboard processor 102 (hereinafter interchangeably referred to as Processor 102).

[0005]

[0004] System 100 further includes a processor 102 and a synchronizer unit 112 communicatively coupled to the first and second sensors 106, 108. The synchronizer unit 112 is configured to receive instructions from the processor 102 and facilitate the synchronized alignment of the first and second sensors 106, 108. In one embodiment, the synchronizer unit 112 is also configured to initiate the simultaneous operation of the first and second sensors 106, 108. In one embodiment, at least one of the first sensors 106 is an optical sensor and an infrared sensor, and at least one of the second sensors 108 includes a microwave sensor. As can be recognized, compared to the conventional sensor systems discussed in the background art section of this document, system 100 includes an additional sensing feature, which is infrared sensing. Furthermore, the synchronizer unit 112 facilitates the simultaneous operation of the first and second sensors 106, 108, as well as their synchronized alignment toward the sample area of ​​the topology under observation.

[0006]

[0005] In pixel-level fusion, corresponding pixels in both datasets are combined using certain mathematical operations to generate a new, more informative pixel. To perform high-quality pixel-level fusion, both datasets must be spatially and temporally aligned so that any pixel in one dataset overlaps as much as possible with its corresponding pixel in the other dataset. Such spatially and temporally aligned datasets are called correlated datasets.

[0007]

[0006] Thus, colregistration is the process by which datasets acquired from both sensors are spatially and temporally aligned with one another, so that corresponding pixels in both datasets point to the same object in the sampled area. This makes pixel-level fusion possible, where corresponding pixels from both datasets are combined. In the case of decision-level fusion or feature-level fusion, colregistration is not essential because they do not interact with pixels in both datasets simultaneously. As explained earlier, this leads to a loss of detail and specificity that can only be seen at the pixel level. For example, when mapping ships in the sea, decision-level fusion would simply compare the fact that dataset 1 and dataset 2 mapped the same number of ships in the sea. Feature-level fusion would compare data acquired from different features in the image, so that each ship is mapped to the other dataset, giving details about its location. Pixel-level fusion gives much more detail regarding area and features, with each pixel mapped to the other dataset. This results in insights such as the size and volume of each ship, the number of containers present, etc. Thus, it can be seen that pixel-level fusion enables new information that can be accessed, and therefore new insights that can be derived.

[0008]

[0007] Figure 1B shows a schematic diagram of an exemplary embodiment of system 100 according to the present invention. As can be seen in Figure 1B, sensors 106 and 108 are mounted on a transporter V having an altitude above the planet's crust C. In Figure 1B, it can be seen that sensors 106 and 108 are aligned to simultaneously sense the planet's topology.

[0009]

[0008] Figure 2 shows a schematic diagram of an exemplary embodiment of system 100 according to the present invention. See Figures 1 and 2 below. The first step in triggering the operation of system 100 is to command the onboard processor 102 that observation of a particular sample area is required. Upon receiving the command, the onboard processor 102 triggers synchronization of the first and second sensors 106, 108 via the synchronizer unit 112. As previously mentioned, the synchronizer unit 112 may be configured to facilitate simultaneous operation, along with synchronized alignment of the first and second sensors 106, 108 toward the sample area of ​​topology under observation.

[0010]

[0009] In one embodiment, as shown in Figure 2, the beam centers of the first sensor 106 and the second sensor 108 in the cross-track direction are aligned, and data acquisition begins simultaneously. An advantageous aspect of such a feature is that it facilitates the acquisition of spatially and temporally aligned datasets of the requested parameters. According to another embodiment, to facilitate smooth pixel-level correlation of the datasets, the number of pixels in the first sensor 106 (optical sensor and infrared sensor) dataset is a multiple of the number of pixels in the microwave sensor dataset. According to yet another embodiment, an advantageous aspect of having simultaneous operation of the first and second sensors 106, 108 together with synchronized alignment is that it enables the capture of pixels aligned in timestamp and azimuth components, thereby ultimately facilitating smooth pixel-level correlation of different datasets from the two sensors.

[0011]

[0010] According to one embodiment, the first and second sensors 106, 108 are configured on at least one of an aircraft, a spacecraft, and a satellite. More specifically, the first and second sensors 106, 108 may be mounted on any transport that can travel at an altitude above the planet's crust.

[0012]

[0011] Referring again to Figure 2, once the first and second sensors 106, 108 have captured spatially and temporally consistent datasets, these are then received and processed by the onboard processor 102. As previously mentioned, the processor 102 facilitates the processing of the datasets to perform pixel-level colregistration of the datasets acquired by two different sensors configured for optical sensing, infrared sensing, and microwave sensing. Pixel-level colregistration of the datasets facilitates more efficient post-processing to obtain more accurate and meaningful datasets compared to conventional systems.

[0013]

[0012] Figure 3 shows a schematic diagram of a synchronizer unit 112 used in a system 100 according to one embodiment of the present invention. The synchronizer unit 112 according to one embodiment of the present invention includes a synchronizer control unit 114. At least one motion sensor 116 is communicatively coupled to the synchronizer control unit 114 and to first and second sensors 106, 108 for detecting the positions of the first and second sensors. The synchronizer unit 112 further includes at least one actuator 118 communicatively coupled to the synchronizer control unit 114. The actuator 118 is also coupled to the first and second sensors 106, 108 to facilitate the synchronized and aligned orientation of the first and second sensors toward the sample area in order to sense a spatially and temporally aligned dataset.

[0014]

[0013] The motion sensor 116 is configured to detect the precise positions of sensors 106 and 108. Position information is fed back to the synchronizer control unit 114 as feedback, and based on this, the synchronizer control unit 114 controls the actuator 118 to facilitate the synchronized and aligned orientation of the first and second sensors 106 and 108.

[0015]

[0014] However, the synchronizer control unit 114 is also communicatively coupled to the transport aircraft stabilization unit 402 of the transport aircraft to which the system 100 may be mounted. This ensures that the synchronizer control unit 114 takes into account not only the position of the sensors but also the position of the transport aircraft when facilitating the synchronized and aligned orientation of the first and second sensors 106, 108 toward the desired sample area.

[0016]

[0015] Figure 4 shows a block diagram illustrating a method 500 (hereinafter referred to as Method 500) for sensing planetary topography according to one embodiment of the present invention. Referring to Figure 5, in block 502, the method includes the step of receiving a capture command. In one embodiment, the capture command is received via an onboard processor 102. The capture command may be provided to the onboard processor 102 via a remote server which may be set up on the surface, or by an internal trigger logic circuit provided within the onboard processor 102, or by a crew member in a transport vehicle to which the system 100 is installed.

[0017]

[0016] In block 504, method 500 includes the step of activating a synchronizer unit. More specifically, at least one first sensor and at least one second sensor are configured on at least one transporter that moves at an altitude above the planetary crust to sense the topography of the planetary sample area. The step of activating the synchronizer unit includes facilitating the synchronized and aligned orientation of at least one first sensor and at least one second sensor toward the sample area in order to sense a spatially and temporally aligned dataset.

[0018]

[0017] In block 506, method 500 includes simultaneously operating a visible sensor (also called an optical sensor, an infrared sensor, and a first sensor) and a microwave sensor (also called a second sensor) to obtain a spatially and temporally consistent dataset.

[0019]

[0018] In block 508, method 500 includes the step of receiving and processing a spatially and temporally aligned dataset in order to perform pixel-level colregistration of the spatially and temporally aligned dataset as seen in block 510. According to one embodiment of the present invention, this step is performed by the onboard processor 102 of system 100.

[0020]

[0019] As can be summarized from the above description, system 100 facilitates pixel-level colregistration of the datasets acquired by the first and second sensors 106 and 108. Furthermore, in order to perform smooth pixel-level colregistration of the datasets acquired by the first and second sensors, system 100 effectively utilizes the complementary properties of the individual sensors and combines the individual datasets of the two sensors.

[0021]

[0020] An advantageous aspect of system 100 is that by housing individual sensors within a common system, it facilitates "simultaneous" data acquisition in the same location. This is not currently possible because individual sensor datasets currently come from different sources. As a result, the completeness and consistency of the datasets are maintained.

[0022]

[0021] However, the optical sensor 106 cannot sense through clouds, and therefore, much of the acquired data becomes less meaningful due to the presence of cloud occlusion in the acquired data. Typically, all datasets containing more than 10% cloud occlusion are not used for data processing, analysis, and insights. Therefore, by using the infrared sensing features of the radar sensor 110 and the first sensor, it is possible to acquire data even in cloudy conditions, and the 10% cloud occlusion threshold can be further raised, increasing the possibility of handling situations with more cloud occlusion. As a result, the amount of meaningful data captured increases significantly.

[0023]

[0022] System 100 according to an embodiment of the present invention has a variety of applications that leverage Earth observation and remote sensing. The applications of System 100 can be broadly classified into three use cases: asset detection, asset monitoring (inspection / tracking), and change detection. These three use cases can be applied to a variety of industries, including but not limited to agriculture, real estate, public works, defense, finance, supply chain, mining, infrastructure, and disaster management. While optical data is widely used to visually understand the area in question, radar data can help reveal deeper insights that are not possible to obtain from optical data alone. New datasets can be used to capture both the color and geometric shape of the object being sensed, providing a better view of the sample area in question.

[0024]

[0023] In the case of agriculture, the system 100 can be used to generate pixel-level correlations of a dataset that can help detect soil type (e.g., color) and soil moisture content, which can help in formulating suitable fertilization and irrigation protocols for the sample area in question.

[0025]

[0024] Another further application of System 100 could be in forest mapping. Pixel-level correlation of a dataset can facilitate monitoring of forest type (tree shape) and plant health (based on leaf color), thereby helping to track the level of deforestation in a sample area of ​​interest.

[0026]

[0025] Another application of system 100 could be the detection and mapping of camouflaged objects within a sample area of ​​interest. Pixel-level correlation of datasets acquired by sensors 106, 108 may also prove useful in mapping camouflaged objects, where optical sensors alone have limitations. Often, radar sensors can pinpoint anomalies in an area, regardless of camouflage, but they cannot describe objects with as much precision. One real-time example comes from Africa, where a water management system in a rural settlement area was planned based on this application. The dwellings were a mix of houses with metal roofs and thatched roofs. The latter were camouflaged with the ground surface, while the former were captured by radar sensors. By selecting these locations and then acquiring them in detail using optical sensors across these areas, an idea of ​​the population and covered area was gained. This saved a lot of time, money, and effort compared to conducting manual ground surveys across the area. Radar sensors also have the ability to detect groundwater levels. The new dataset acquired by System 100 can thus provide a visual map of the area, including the groundwater level at that particular location. Doing this using data from conventional sources would involve many errors and complexities, as already explained earlier.

[0027]

[0026] Various characteristics and advantageous details are illustrated in the accompanying drawings and will be fully clarified with reference to the embodiments / aspects detailed in the foregoing description. Descriptions of techniques, methods, components and devices well known to those skilled in the art, or descriptions thereof that form common general knowledge in the field to which the present invention belongs, are not described and / or introduced for the purpose of focusing on the present invention and so as not to obscure the present invention and its advantageous features. Meanwhile, the present invention and its features described herein in the detailed description and specific examples are given by way of illustration only, not by way of limitation. It should be understood that those skilled in the art may and can conceive of various alternative substitutions, modifications, additions, and / or rearrangements that are considered to be within the spirit and / or scope of the underlying inventive concept.

[0028]

[0027] As used herein, the word "comprise", or variations thereof such as "comprises" or "comprising", implies the inclusion of a stated element, integer or step, or group of elements, integers or steps, but does not imply the exclusion of any other element, integer or step, or group of elements, integers or steps.

[0029]

[0028] Furthermore, the use of the expression "at least" or "at least one" suggests the use of one or more elements, materials or quantities, as the case may be in embodiments of the present invention, to achieve one or more desired objects or results.

Claims

1. A sensor system for sensing planetary topography, At least one onboard processor, To sense the topography of the sample area of ​​the planet, at least one first sensor and at least one second sensor are configured on at least one transporter moving at an altitude above the planet's crust, and the at least one first sensor and at least one second sensor are communicatively coupled to at least one onboard processor, At least one memory that is communicably coupled to the at least one onboard processor, and when executed by the at least one onboard processor, i. To sense a spatially and temporally consistent dataset, the synchronized and aligned orientation of the at least one first sensor and the at least one second sensor toward the sample area is facilitated, and the synchronized and aligned orientation of the at least one first sensor and the at least one second sensor is facilitated via a synchronizer unit communicably coupled to the at least one onboard processor, and ii. Receiving and processing the spatially and temporally aligned dataset in order to perform pixel-level correlation of the spatially and temporally aligned dataset. Memory that stores executable instructions to perform the action, The system includes, wherein the at least one first sensor includes an optical sensor and an infrared sensor, and the at least one second sensor includes a microwave sensor. A sensor system in which, in order to spatially and temporally align the pixels in the datasets of the optical sensor and the infrared sensor with the pixels in the dataset of the microwave sensor, the number of pixels in the datasets of the optical sensor and the infrared sensor is a multiple of the number of pixels in the dataset of the microwave sensor, which is collected and aligned simultaneously with the datasets of the optical sensor and the infrared sensor.

2. The sensor system according to claim 1, wherein the transport vehicle is one of a spacecraft, an aircraft, and a satellite.

3. The sensor system according to claim 2, wherein the beam centers of the first sensor and the second sensor in the direction toward the sample area are aligned.

4. The synchronizer unit, Synchronizer control unit, At least one motion sensor communicatively coupled to the synchronizer control unit, the at least one motion sensor coupled to the at least one first sensor and the at least one second sensor for detecting the position of the at least one first sensor and the at least one second sensor, At least one actuator communicatively coupled to the synchronizer control unit, and at least one actuator coupled to the at least one first sensor and the at least one second sensor to facilitate the synchronized and aligned orientation of the at least one first sensor and the at least one second sensor toward the sample area in order to sense a spatially and temporally aligned dataset, The sensor system according to claim 1, including the following:

5. The sensor system according to claim 1, wherein the at least one first sensor and the at least one second sensor are configured on at least one transporter.

6. A method performed by a processor for sensing the topology of a planet, The steps include configuring at least one first sensor and at least one second sensor, which are configured on at least one transporter moving at an altitude above the planet's crust, in order to sense the topography of the sample area of ​​the planet, Steps to facilitate the synchronized and aligned orientation of the at least one first sensor and the at least one second sensor toward the sample area in order to sense a spatially and temporally consistent dataset, To generate a pixel-level correlated dataset corresponding to the spatially and temporally correlated dataset, the steps include receiving and processing the spatially and temporally correlated dataset, The system includes, wherein the at least one first sensor includes an optical sensor and an infrared sensor, and the at least one second sensor includes a microwave sensor. A method for spatially and temporally aligning pixels in the optical sensor and infrared sensor datasets with pixels in the microwave sensor dataset, wherein the number of pixels in the optical sensor and infrared sensor datasets is a multiple of the number of pixels in the microwave sensor dataset, which is collected and aligned simultaneously with the optical sensor and infrared sensor datasets.

7. The beam centers of the first sensor and the second sensor in the direction toward the sample area are aligned. The method according to claim 6.

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