Range Detection

Abstract

According to an exemplary aspect of the present invention, an apparatus is provided configured to store information defining a set of criteria areas, at least each criteria area having a location, a shape and a geographic size, acquire range detection data including a plurality of data items, each data item having a location and a size, assign at least a portion of the data items to the set of criteria areas such that sizes of data items having locations within the same criteria area are summed, and apply a threshold value to select from among the criteria areas a second set of criteria areas having a combined size exceeding the threshold value.

Description

[Technical Field]

[0001] The present disclosure relates to managing range sensing data from radar, lidar, and the like. [Background technology]

[0002] Positioning of objects is often performed using Global Navigation Satellite Systems (GNSS), i.e. satellite positioning such as GPS or the Galileo constellation, or alternatively, positioning can be performed using the positioning capabilities of a cellular communication network, for example.

[0003] For example, autonomous and semi-autonomous vehicles require accurate positioning mechanisms to ensure the safety of the people inside such vehicles and the nearby routes they traverse, and vehicle navigation applications require positioning information to provide meaningful navigation advice to drivers. Summary of the Invention [Means for solving the problem]

[0004] According to some aspects, the subject matter of the independent claims is provided. Some embodiments are defined in the dependent claims.

[0005] According to a first aspect of the present disclosure, there is provided an apparatus comprising at least one processing core and at least one memory including computer program code, wherein the at least one memory and the computer program code are configured to cause the apparatus to at least: store information defining a set of reference areas, each reference area having a position, a shape, and a geographical size; acquire range detection data including a plurality of data items, each data item having a position and a size; assign at least some of the data items to the set of reference areas such that sizes of data items having positions within the same reference area are summed; and apply the threshold to select from the reference areas a second set of reference areas having a combined size that exceeds a threshold.

[0006] According to a second aspect of the present disclosure, there is provided a method including the steps of: storing information defining a set of reference areas, each reference area having a location, a shape, and a geographical size; acquiring range detection data including a plurality of data items, each data item having a location and a size; assigning at least some of the data items to the set of reference areas such that the sizes of data items having locations within the same reference area are summed; and applying the threshold to select from the reference areas a second set of reference areas having a combined size that exceeds a threshold.

[0007] According to a third aspect of the present disclosure, there is provided a non-transitory computer-readable medium having stored thereon a set of computer-readable instructions that, when executed by at least one processor, causes an apparatus to at least store information defining a set of criteria areas, each criteria area having a location, a shape, and a geographical size; acquire range detection data including a plurality of data items, each data item having a location and a size; assign at least some of the data items to the set of criteria areas such that sizes of data items having locations within the same criteria area are summed; and apply the threshold to select from the criteria areas a second set of criteria areas having a combined size that exceeds a threshold. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 illustrates an exemplary system in accordance with at least some embodiments of the present invention. [Figure 2A] ~ [Figure 2B] FIG. 1 illustrates landmark fitting in accordance with at least some embodiments of the present invention. [Figure 3] FIG. 1 illustrates an example of a device capable of supporting at least some embodiments of the present invention. [Figure 4] FIG. 1 illustrates signaling in accordance with at least some embodiments of the present invention. [Figure 5] 1 is a flowchart of a method in accordance with at least some embodiments of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0009] An occupancy grid containing reference areas, such as squares or hexagons, is employed to assist in distinguishing between landmarks and spurious reflections in the range sensing data. Specifically, reflections in the range sensing data are assigned to reference areas of the grid, and then the magnitudes of such reflections are summed to arrive at an integrated reflection magnitude for the or each reference area. The integrated reflection magnitude may be used in landmark-based navigation; for example, a threshold may be applied to the integrated reflection magnitude for a reference area so that spurious reflections that do not affect navigation can be ignored.

[0010] FIG. 1 illustrates an exemplary system in accordance with at least some embodiments of the present invention. A range detector 110, which may be, for example, a radar or lidar device, emits energy 103 and records range data based on the reflection of the energy 103 from targets within the field of view of the range detector 110. To accomplish this, the range detector 110 includes a transmitter that transmits the energy 103 and a receiver that detects portions of the energy 103 that are reflected back toward the range detector 110. Alternatively or in addition to a radar or lidar, the range detector may be, for example, a sonar. Generally, a single pulse of energy 103 transmitted from the range detector 110 may produce multiple distinct reflections from multiple objects 102 within its field of view. An advantage of using radar is its robustness against changing weather conditions. Radar also provides a high degree of accuracy in determining the direction from which reflections return to the radar.

[0011] Suitable radars operate, for example, in the 24 GHz and / or 77 GHz bands. Radars as used herein may use more than one frequency. In some embodiments, a hyperspectral range detector 110 is used.

[0012] When in use, the range detection device 110 generates range detection data. The range detection data includes multiple data items, each having a position and a size. Each data item characterizes the detection of an object 102. Each data item represents a detected reflection of energy 103 received by the range detection device 110. Reflections may originate from people and animals within the field of view of the range detection device 110, as well as from objects such as buildings, vehicles, streetlights, and debris on the ground. Because people may generate multiple reflections, they may appear in the range detection data as a set of geographically clustered objects 102.

[0013] The position of each data item may be expressed in any suitable manner, for example, as Cartesian coordinates x, y in a coordinate system within the field of view of the range detector 110. Alternatively, the position within the field of view may be expressed, for example, as a distance from the range detector 110 and a sweep angle that fixes the direction in which the corresponding object 102 is located.

[0014] The magnitude of each data item indicates the strength of the return recorded by the range finding device 110. If the range finding device 110 is a radar, the magnitude may be referred to as the radar cross section. Generally, a large reflective object 102 will produce a strong return and therefore a high magnitude, however, the shape of the object 102 and environmental conditions may affect the exact magnitude, and a single large object 102 may produce more than one return and therefore more than one data item in the range finding data.

[0015] In the system of FIG. 1 , a grid 100 is defined. The grid 100 is composed of a set of reference areas 101, which are square in the system of FIG. 1 but may be hexagonal or of other shapes depending on the particular implementation. In the grid of FIG. 1 , the reference areas 101 are adjacent to each other, with no gaps between adjacent reference areas 101. In other embodiments, adjacent reference areas 101 may have gaps between them, which is useful in use cases where it is known that certain regions of the field of view of the range detection device are free of objects of interest 102. For example, in such use cases, the reference areas 101 may cover roads or paths of travel, while blocks of forest or buildings adjacent to the roads may not overlap with the reference areas 101. The grid 100 may be referred to as an occupancy grid.

[0016] Each reference area 101 has a position, a shape, and a geographical size. The information defining the set of reference areas may specify that all reference areas 101 are square and, for example, have the same size. In such a case, the position of the square may be defined in an x, y coordinate system. In a more general case, the reference areas 101 of the grid 100 may be of different sizes and / or shapes. For example, the reference areas 101 directly in front of the vehicle may be small, while the reference areas located more peripherally may be larger. If the reference areas 101 are square or hexagonal, their sides may be, for example, 10, 20, or 30 centimeters. In some cases, the length and / or depth of the grid 100 may be, for example, 100 meters or 200 meters.

[0017] Once the range detection device 110 acquires the range detection data, the range detection device, a device such as a vehicle or vehicle component in which the range detection device is configured, or a separate computing board 120 can assign the data items of the range detection data, or at least some of them, to a reference area. For example, if part of the object 102 is not in the reference area 101 of the grid 100, only some of the data items of the range detection data may be assigned.

[0018] In particular, this involves determining, for each data item to be assigned, a reference area 101 that contains the location of that data item. Depending on the implementation, this determination may require performing appropriate coordinate transformations. If an object 102 is located within a particular reference area 101, the reflection of energy 103 generated by this object 102 is located within this particular reference area 101 by the range detection device 110. This location may be correlated with the location, size, and shape of the reference areas 101 to find which of the reference areas 101 contains the location of the data item, and therefore the location of the object 102 corresponding to the data item.

[0019] When or during the allocation of data items of range detection data to reference areas 101, the magnitudes of the data items for each reference area 101 are summed. In this regard, the sum may include all data items so mapped, even if their magnitudes are very small. In some embodiments, to avoid overflow of the sum, scaling to an appropriate range, such as 0-100, is performed. Such scaling may be, for example, summedMagnitude=summedMagnitude+(dataItemMagnitude[i] / maxValue). * It can be implemented as a sum over i, such as 100, where maxValue is the maximum output magnitude value of the range detector and dataItemMagnitude is the reflected magnitude actually sensed for the data item.

[0020] In some embodiments, the summing includes summing magnitudes of data items from two or more sweeps or pulses of a range finding device, hi some embodiments, the summing includes summing magnitudes of data items from two or more pulses of a range finding device, where the range finding device is radar and the pulses are at different frequencies.

[0021] After summing the sizes, a threshold may be applied to the criteria areas 101 to select from among those criteria areas 101 whose summed sizes exceed the threshold. The thus selected criteria areas form a second set of criteria areas. These criteria areas 101, i.e., the second set of criteria areas, may then be considered as landmark candidates, as will be described in more detail with reference to FIG. 2. Landmark-based navigation may be employed in autonomous or semi-autonomous vehicles, such as automobiles. In the assignment, a data item may be associated with a criteria area by linking to or being placed in a data structure having a similar structure to the set of criteria areas. Alternatively, a link from the data item to the set of criteria areas may be established to achieve the assignment.

[0022] In some embodiments, landmark-based navigation using range sensing data is employed as a response when satellite positioning is determined to be unavailable due to, for example, power outages, indoor conditions, jamming, etc.

[0023] In addition to landmark recognition, the disclosed system can also be used for human detection. Specifically, humans may appear in radar data as a localized set of several small-magnitude reflections. The sum of these reflections may not necessarily have a very high radar cross section, but the presence of multiple reflections close to each other may be considered a potential human detection. Therefore, once the magnitudes are summed into a reference area, a separate consideration may be whether the reference area has a number of data items that exceeds a threshold for human detection, even if the summed magnitude of the reference area 101 does not exceed the threshold for landmark detection, as described above. In some embodiments, the threshold for landmark selection is also employed for human detection, while in other embodiments, a separate, lower threshold is employed for human detection. For example, if a human is at risk of being hit by a vehicle, a warning may be presented to the user to confirm the presence of a human. Depending on the size of the reference area, a cluster of reflections generated by a human may span several adjacent reference areas 101.

[0024] 2A and 2B are diagrams illustrating landmark fitting in accordance with at least some embodiments of the present invention. Grid 100 in FIG. 2A corresponds to grid 100 in FIG. 1. Objects 102 are not shown in FIG. 2; rather, reference areas 101 having a sum of magnitudes exceeding the landmark detection threshold are colored black. In other words, the black reference areas 101 are landmark candidates, i.e., a second set of reference areas. As can be inferred by reference to the grid in FIG. 1, one of the landmark candidates in the second set includes four reflections in FIG. 1, another includes three reflections, and a third is a single reflection whose magnitude alone exceeds the landmark detection threshold. The single reflection may be, for example, a reflection from a metal pole.

[0025] The grid is thus used to eliminate duplicate detections of the same object and to accumulate reflected energy from objects to increase the likelihood of detection from range detection data.

[0026] FIG. 2B shows known landmarks in the area from which range detection data was acquired. The general area in which device 110 or 120 is located may be known from inertial data, possibly in combination with satellite positioning data from before satellite positioning became unavailable. The landmark data includes the specific location of at least one landmark and, optionally, the expected relative size of the landmark. The landmark data may also characterize how the size of the landmark changes as a function of the angle at which the landmark is detected. In other words, some landmarks may have a large magnitude, such as a radar cross section, in a particular direction, which may be used in matching detected landmark candidates with the landmark data. In the landmark data shown in FIG. 2B, there are three landmarks 210, 220, and 230, as well as a road 240.

[0027] The landmark data may be fitted or matched to the detected landmark candidates, i.e., a second set of reference areas, e.g., using a least-squares method, to obtain alignment between the landmark candidates and the landmarks recorded in the landmark data. In the situation of Figures 2A and 2B, because the landmark data identifies the location of road 240 relative to landmarks 210, 220, and 230, aligning the landmark candidates to the landmarks in the landmark data allows for road 240 to be used. The three landmark candidates in Figure 2A are well aligned with the landmarks in Figure 2B. For example, the relative distances and angles between the landmarks and the landmark candidates are the same, resulting in a reliable match.

[0028] It should be emphasized that the second set of landmark candidates may include spurious candidates due to transient events, such as parked vehicles or tractors. Similarly, a landmark may be missing from the range detection data despite being present in the field of view if, for example, an energy absorbing element is between the range detection device 110 and the landmark and the sum of the magnitudes from the landmark is less than the landmark detection threshold. However, when multiple landmarks are used, these issues do not prevent the candidate from being aligned to the actual landmark. In some cases, alignment may be achieved with a single landmark if the surroundings are not too cluttered.

[0029] An important example of landmark fitting is a landmark pattern such as metal utility poles placed at regular intervals along the road. In such a case, a road may be detected by matching the landmark pattern to the landmark candidate pattern, without matching each landmark to each candidate.

[0030] The second set of candidate landmarks may be matched to known landmarks using an optimization algorithm such as the Simplex algorithm, Newton's algorithm, or the Levenberg-Marquardt algorithm. Landmark locations or landmark pattern parameters may be obtained from a database external to range detection device 110 or computing board 120.

[0031] FIG. 3 illustrates an exemplary device capable of supporting at least some embodiments of the present invention. Shown is device 300, which may comprise, for example, range detection device 110 or computing board 120 of FIG. 1 . Device 300 includes processor 310, which may comprise, for example, a single-core or multi-core processor, where a single-core processor comprises one processing core and a multi-core processor comprises two or more processing cores. Processor 310 may generally comprise a controller. Processor 310 may comprise two or more processors. Processor 310 may also be a controller. The processing core may comprise, for example, a Cortex-A8 processing core manufactured by ARM Holdings, Inc. or a Zen processing core designed by Advanced Micro Devices, Inc. Processor 310 may comprise at least one Qualcomm Snapdragon processor and / or an Intel Core processor. Processor 310 may comprise at least one application-specific integrated circuit (ASIC). The processor 310 may comprise at least one field programmable gate array (FPGA). The processor 310 may be a means for storing, retrieving, allocating, applying, etc., for performing steps of the methods in the apparatus 300. The processor 310 may be configured to perform operations at least in part according to computer instructions.

[0032] The device 300 may include a memory 320. The memory 320 may include random access memory and / or permanent memory. The memory 320 may include at least one RAM chip. The memory 320 may include, for example, solid-state memory, magnetic memory, optical memory, and / or holographic memory. The memory 320 may be at least partially accessible to the processor 310. The memory 320 may be at least partially located within the processor 310. The memory 320 may be a means for storing information. The memory 320 may include computer instructions configured to cause the processor 310 to execute a particular operation. When computer instructions configured to cause the processor 310 to perform the particular operation are stored in the memory 320 and the entire device 300 is configured to run under the direction of the processor 310 using the computer instructions from the memory 320, the processor 310 and / or at least one processing core thereof may be considered to be configured to perform the particular operation. The memory 320 may comprise, at least partially, the processor 310. The memory 320 may be at least partially external to the device 300 but accessible to the device 300 .

[0033] Apparatus 300 may include a transmitter 330. Apparatus 300 may include a receiver 340. Transmitter 330 and receiver 340 may be configured to transmit and receive information, respectively, according to at least one cellular or non-cellular standard. Transmitter 330 may include two or more transmitters. Receiver 340 may include two or more receivers. Transmitter 330 and / or receiver 340 may be configured to operate according to, for example, Global System for Mobile Communications (GSM), Wideband Code Division Multiple Access (WCDMA), 5G, Long Term Evolution (LTE), IS-95, Wireless Local Area Network (WLAN), Ethernet, and / or Worldwide Interoperability for Microwave Access (WiMAX) standards.

[0034] The device 300 may include a user interface (UI) 360. The UI 360 may include at least one of a display, a keyboard, a touchscreen, a vibrator arranged to send signals to a user by vibrating the device 300, a speaker, and a microphone. A user may be able to operate the device 300 via the UI 360, for example, to set navigation parameters or thresholds.

[0035] Processor 310 may include a transmitter arranged to output information from processor 310 to other devices located within device 300 via electrical leads within device 300. Such a transmitter may, for example, include a serial bus transmitter arranged to output information via at least one electrical lead to memory 320 for storage therein. As an alternative to a serial bus, the transmitter may include a parallel bus transmitter. Similarly, processor 310 may include a receiver arranged to receive information from other devices located within device 300 via electrical leads within device 300 into processor 310. As an alternative to a serial bus, the receiver may include a serial bus receiver arranged to receive information via at least one electrical lead from receiver 340 for processing by processor 310. As an alternative to a serial bus, the receiver may include a parallel bus receiver. Device 300 may include additional devices not shown in FIG. 3 .

[0036] The processor 310, memory 320, transmitter 330, receiver 340, and / or UI 360 may be interconnected by electrical leads within device 300 in a number of different ways. For example, each of the aforementioned devices may be individually connected to a master bus within device 300 so that the devices can exchange information. However, those skilled in the art will appreciate that this is only one example, and that depending on the embodiment, various methods of interconnecting at least two of the aforementioned devices may be selected without departing from the scope of the present invention.

[0037] Figure 4 is a diagram illustrating signaling in accordance with at least some embodiments of the present invention. The vertical axis shows a satellite navigation constellation (SAT) on the left, a computing board 120 in the middle, and a landmark database DB on the right. Time progresses from top to bottom. In the embodiment of Figure 4, the computing board 120 is mounted on a vehicle.

[0038] In phase 410, the vehicle navigates using positioning from a satellite navigation constellation (SAT). For example, the computing board 120 may provide the driver with a graphical map display along with turning advice. In phase 420, the computing board 120 determines that sufficient data is no longer available from the satellite navigation, and in response, the computing board 120 requests local landmark information from the database DB. The request in phase 430 may include, for example, the most recent position of the computing board 120 as determined by the satellite navigation before the connection to the satellite navigation was lost.

[0039] In phase 440, database DB responds by providing the requested landmark information to computing board 120. Then, in phase 450, computing board 120 uses the landmark-based navigation method as described herein above in relation to Figures 2A and 2B. To enable this, the vehicle also includes range detection device 110 as described herein above in relation to Figure 1.

[0040] The mechanisms disclosed herein allow vehicles, such as autonomous vehicles, to use landmarks for more accurate positioning than simply filtering radar detections. Accumulating magnitudes allows the method to be used in environments where the apparent size of landmarks changes, such as when they become dirty or damaged. Also, analyzing the number of returns, as described above, makes human detection more reliable.

[0041] 5 is a flowchart of a method in accordance with at least some embodiments of the present invention. The illustrated method phases may be performed on the computing board 120, the vehicle, or a controller configured to control its functions when installed therein.

[0042] Phase 510 includes storing information defining a set of criteria areas, each of which has a location, a shape, and a geographic size. Phase 520 includes acquiring range detection data including a plurality of data items, each of which has a location and a size. Phase 530 includes assigning at least some of the data items to the set of criteria areas such that the sizes of data items having locations within the same criteria area are summed. Finally, phase 540 includes applying a threshold to select from the criteria areas a second set of criteria areas having a combined size exceeding the threshold.

[0043] It will be understood that the disclosed embodiments of the invention are not limited to the particular structures, process steps, or materials disclosed herein, but extend to equivalents thereof recognized by those skilled in the relevant arts. It is also to be understood that the terminology used herein is used for the purpose of describing particular embodiments only, and is not intended to be limiting.

[0044] Throughout this specification, reference to an embodiment or embodiments means that a particular feature, structure, or characteristic described in connection with an embodiment is included in at least one embodiment of the present invention. Thus, the appearance of the phrase "in one embodiment" or "in an embodiment" in various places throughout this specification do not necessarily all refer to the same embodiment. For example, when a numerical value is referred to using terms such as about, substantially, etc., the exact numerical value is also disclosed.

[0045] In this specification, a plurality of items, structural elements, components, and / or materials may be presented in a common list for convenience. However, these lists should be construed as though each member of the list is individually identified as a separate and unique member. Accordingly, the individual members of such lists should not be construed as de facto equivalents of other members of the same list solely based on their presentation in a common group, absent indications to the contrary. Furthermore, various embodiments and examples of the present invention may be referred to herein, along with alternatives for the various components thereof. It is understood that such embodiments, examples, and alternatives are not to be construed as de facto equivalents of each other, but rather as separate and autonomous manifestations of the present invention.

[0046] Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. The foregoing description provides numerous specific details, such as examples of lengths, widths, shapes, etc., to provide a thorough understanding of embodiments of the present invention. However, one skilled in the relevant art will recognize that the present invention can be practiced without one or more of the specific details, or with other methods, components, materials, etc. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of the present invention.

[0047] While the above-described embodiments illustrate the principles of the present invention in one or more particular applications, it will be apparent to those skilled in the art that numerous changes in form, use, and details of implementation can be made without the exercise of inventive faculty and without departing from the principles and concepts of the present invention. Accordingly, it is not intended that the present invention be limited except as by the scope of the claims set forth below.

[0048] In this specification, the verbs "comprise" and "include" are used as open limitations which neither exclude nor require the presence of any unrecited features. Features recited in the dependent claims may be freely combined with one another, unless expressly stated otherwise. Furthermore, it is to be understood that throughout this specification the use of "a" or "an", i.e., the singular, does not exclude the plural. [Appendix 1] 1. An apparatus comprising at least one processing core and at least one memory containing computer program code, the at least one memory and the computer program code being transmitted by the at least one processing core to the apparatus in such a way that at least: storing information defining a set of reference areas, each reference area having a location, a shape, and a geographical size; acquiring range detection data including a plurality of data items, each data item having a position; assigning at least some of said data items to sets of said criteria areas such that data items having positions within the same criteria area are summed; each data item having a magnitude, and summing the data items includes summing the magnitudes, and the device applies the threshold to select, from among the criteria areas, a second set of criteria areas having a combined magnitude that exceeds a threshold; matching the locations of the second set of reference areas to known landmark locations and employing the second set of reference areas for landmark-based navigation of the vehicle; An apparatus characterized in that [Appendix 2] 2. The device of claim 1, wherein the range detection data is radar data or lidar data. [Appendix 3] 3. The apparatus of claim 1 or 2, wherein the apparatus is configured to match a pattern of locations of at least two or three reference areas of the second set to a pattern of known landmark locations. [Appendix 4] 4. The device of any one of claims 1 to 3, wherein the device is configured to obtain the known landmark locations from a database external to the device. [Appendix 5] The apparatus of any one of claims 1 to 4, wherein the apparatus is configured to classify the reference area as a potential human location from among the second set of data items assigned with a magnitude less than a second threshold. [Appendix 6] 6. The apparatus of claim 1, wherein allocating at least some of the data items to the set of criteria areas does not involve using a size threshold. [Appendix 7] 7. The device according to any one of claims 1 to 6, wherein the vehicle navigation is an automobile navigation. [Appendix 8] 8. The device of claim 1, wherein the device is configured to obtain the range detection data and select the second set of criteria areas in response to determining that satellite navigation is not available. [Appendix 9] 1. A method comprising: storing information defining a set of criteria areas, each criteria area having a location, a shape, and a geographical size; acquiring range detection data including a plurality of data items, each data item having a position; assigning at least some of the data items to a set of criteria areas such that data items having a position within the same criteria area are summed; Including, each data item having a magnitude, and summing the data items includes summing the magnitudes, the method comprising: applying the threshold to select from among the criteria areas a second set of criteria areas having a combined magnitude that exceeds a threshold; matching locations of the second set of reference areas to known landmark locations and employing the second set of reference areas for landmark-based navigation of the vehicle; The method further comprising: [Appendix 10] 10. The method of claim 9, wherein the range detection data is radar data or lidar data. [Appendix 11] 11. The method of claim 9 or 10, wherein the matching step comprises matching a pattern of locations of at least two or three reference areas of the second set to a pattern of known landmark locations. [Appendix 12] 12. The method of any one of claims 9 to 11, further comprising obtaining the known landmark locations from a database external to the device. [Appendix 13] 13. The method of any one of claims 9 to 12, further comprising classifying the reference area as a potential human location from among the second set of data items assigned with a magnitude less than a second threshold. [Appendix 14] 14. The method of any one of claims 9 to 13, wherein the step of assigning at least some of the data items to the set of criteria areas does not include using a size threshold. [Appendix 15] 15. The method according to any one of appendices 9 to 14, wherein the vehicle navigation is an automobile navigation. [Appendix 16] 16. The method of any one of claims 9 to 15, wherein the steps of obtaining range detection data and selecting the second set of criteria areas are performed in response to determining that satellite navigation is unavailable. [Appendix 17] A non-transitory computer-readable medium having stored thereon a set of computer-readable instructions that, when executed by at least one processor, cause an apparatus to at least: storing information defining a set of reference areas, each reference area having a location, a shape, and a geographical size; acquiring range detection data including a plurality of data items, each data item having a position; assigning at least some of said data items to sets of said criteria areas such that data items having positions within the same criteria area are summed; Each data item has a magnitude, and summing the data items includes summing the magnitudes, and the set of computer-readable instructions, when executed, further cause the device to apply the threshold to select a second set of criteria areas from the criteria areas having a combined magnitude that exceeds the threshold, match positions of the second set of criteria areas to known landmark positions, and employ the second set of criteria areas in landmark-based navigation of a vehicle. 10. A computer-readable medium comprising: [Industrial Applicability]

[0049] At least some embodiments of the present invention have industrial applicability in the management of range detection data. [Explanation of symbols]

[0050] GPS Global Positioning System

Claims

1. 1. An apparatus comprising at least one processing core and at least one memory containing computer program code, the at least one memory and the computer program code being transmitted by the at least one processing core to the apparatus in such a way that at least: storing information defining a set of reference areas, each reference area having a location, a shape, and a geographical size; acquiring range detection data including a plurality of data items, each data item having a position; assigning at least some of the data items to the set of reference areas such that the sizes of data items having positions within the same reference area are summed; each data item having a respective magnitude indicative of the intensity of the reflection recorded by the range detection device, summing the magnitudes of the data items includes obtaining an integrated magnitude by summing the intensities of the reflections, the device applying the threshold to select from among the criteria areas a second set of criteria areas having the integrated magnitude exceeding a threshold; matching the locations of the second set of reference areas to known landmark locations and employing the second set of reference areas for landmark-based navigation of the vehicle; An apparatus characterized in that

2. 2. The apparatus of claim 1, wherein the range detection data is radar data or lidar data.

3. 3. An apparatus according to claim 1 or 2, wherein the apparatus is configured to obtain the known landmark locations from a database external to the apparatus.

4. 4. The device according to claim 1, wherein the device is configured to classify the reference area as a potential human location from among the second set to which a plurality of data items having a magnitude smaller than a second threshold are assigned.

5. 5. The device according to any one of claims 1 to 4, characterized in that the vehicle navigation is an automobile navigation.

6. 6. An apparatus according to any preceding claim, wherein the apparatus is configured to obtain the range detection data and select the second set of criteria areas in response to determining that satellite navigation is not available.

7. A method performed by an apparatus, comprising: storing information defining a set of criteria areas, each criteria area having a location, a shape, and a geographical size; acquiring range detection data including a plurality of data items, each data item having a position; allocating at least some of the data items to the set of reference areas such that the sizes of data items having positions within the same reference area are summed; Including, each data item having a respective magnitude indicative of the intensity of a reflection recorded by a range detection device, and summing the magnitudes of the data items comprises obtaining an integrated magnitude by summing the intensities of the reflections, the method comprising the steps of: applying the threshold to select from among the criteria areas a second set of criteria areas having the integrated magnitude exceeding a threshold; matching locations of the second set of reference areas to known landmark locations and employing the second set of reference areas for landmark-based navigation of the vehicle; The method further comprising:

8. 8. The method of claim 7, wherein the range sensing data is radar data or lidar data.

9. 9. The method of claim 7 or 8, further comprising obtaining the known landmark locations from a database external to the device.

10. 10. The method of claim 7, further comprising classifying the reference area as a potential human location from among the second set of data items assigned with a magnitude less than a second threshold.

11. 11. A method according to any one of claims 7 to 10, characterized in that the vehicle navigation is an automobile navigation.

12. 12. A method according to any one of claims 7 to 11, wherein the steps of obtaining range detection data and selecting the second set of criteria areas are performed in response to determining that satellite navigation is unavailable.

13. A non-transitory computer-readable medium having stored thereon a set of computer-readable instructions that, when executed by at least one processor, cause an apparatus to at least: storing information defining a set of reference areas, each reference area having a location, a shape, and a geographical size; acquiring range detection data including a plurality of data items, each data item having a position; assigning at least some of the data items to the set of reference areas such that the sizes of data items having positions within the same reference area are summed; Each data item has a respective magnitude indicative of the intensity of the reflection recorded by the range detection device, and summing the magnitudes of the data items includes summing the intensities of the reflections to obtain an integrated magnitude, and the set of computer readable instructions, when executed, further cause the device to apply the threshold to select a second set of reference areas from the reference areas having the integrated magnitude exceeding the threshold, match positions of the second set of reference areas to known landmark positions, and employ the second set of reference areas in landmark-based navigation of the vehicle.

10. A computer-readable medium comprising:

Images