Patent Application
20150373500
I. Field of the Invention
This disclosure relates generally to systems, apparatus and methods for position or location determination of a mobile device, and more specifically for indoor localization based on multi-hypothesis testing using a plurality of mobile device trajectories.
II. Background
A location context identifier (LCI) is a uniquely identifiable area such as a single floor or a wing of a floor with a single floor map or floor plan. Within an LCI, indoor localization is performed, for example, using a particle filter. LCI disambiguation is the procedure to identify which LCI a mobile device is within so a proper map of the area and the correct assistance data may be downloaded from a server. Once the proper map and correct assistance data are downloaded, an indoor localization engine may start. A localization engine's particle filter uses one RSSI or RTT heatmap per access point (AP). An LCI may correspond to one single-floor building map represented by, for example, a connectivity grid.
Typically, a mobile device determines a current LCI and then requests and receives assistance data. The request may be several bytes but the assistance data may be several kilobytes to several megabytes. there exists a need to reduce data traffic between a mobile device and a server.
Disclosed are systems, apparatus and methods to compute multiple hypotheses for an area identifier, for example, a current location context identifier (LCI). An area identifier, such as an LCI, defines a particular floor or a section of a floor. An access point (AP) is associated with one area identifier. Each mobile device trajectory is computed assuming the mobile device is located at one hypothesized area identifier and using the measurements of the list of APs belong to the one hypothesized area identifier. The current area identifier is based on the best trajectory of the mobile device.
According to some aspects, disclosed is a method to perform hypothesis localization, the method comprising: receiving, for a plurality of specific areas, area information, wherein for each specific area, the area information comprises an identifier, a list of access points (APs), and a map of the specific area; providing a plurality of mobile device trajectories, wherein each trajectory of the plurality of mobile device trajectories corresponds to the list of APs from a hypothesized area; evaluating the plurality of mobile device trajectories; and selecting an area identifier bases on evaluating the plurality of mobile device trajectories.
According to some aspects, disclosed is a device to perform hypothesis localization, the device comprising: a receiver configured to receive, for a plurality of specific areas, area information, wherein for each specific area, the area information comprises an identifier, a list of access points (APs), and a map of the specific area; and a processor coupled to the receiver, wherein the processor is configured to: provide a plurality of mobile device trajectories, wherein each trajectory of the plurality of mobile device trajectories corresponds to the list of APs from a hypothesized area; evaluate the plurality of mobile device trajectories; and select an area identifier bases on evaluating the plurality of mobile device trajectories.
According to some aspects, disclosed is a device to perform hypothesis localization, the device comprising: means for receiving, for a plurality of specific areas, area information, wherein for each specific area, the area information comprises an identifier, a list of access points (APs), and a map of the specific area; means for providing a plurality of mobile device trajectories, wherein each trajectory of the plurality of mobile device trajectories corresponds to the list of APs from a hypothesized area; means for evaluating the plurality of mobile device trajectories; and means for selecting an area identifier bases on evaluating the plurality of mobile device trajectories.
According to some aspects, disclosed is a non-transient computer-readable storage medium, for a device to perform hypothesis localization, including program code stored thereon, comprising program code to: receive, for a plurality of specific areas, area information, wherein for each specific area, the area information comprises an identifier, a list of access points (APs), and a map of the specific area; provide a plurality of mobile device trajectories, wherein each trajectory of the plurality of mobile device trajectories corresponds to the list of APs from a hypothesized area; evaluate the plurality of mobile device trajectories; and select an area identifier bases on evaluating the plurality of mobile device trajectories.
It is understood that other aspects will become readily apparent to those skilled in the art from the following detailed description, wherein it is shown and described various aspects by way of illustration. The drawings and detailed description are to be regarded as illustrative in nature and not as restrictive.
Some embodiments of the invention will be described, by way of example only, with reference to the drawings.
The detailed description set forth below in connection with the appended drawings is intended as a description of various aspects of the present disclosure and is not intended to represent the only aspects in which the present disclosure may be practiced. Each aspect described in this disclosure is provided merely as an example or illustration of the present disclosure, and should not necessarily be construed as preferred or advantageous over other aspects. The detailed description includes specific details for the purpose of providing a thorough understanding of the present disclosure. However, it will be apparent to those skilled in the art that the present disclosure may be practiced without these specific details. In some instances, well-known structures and devices are shown in block diagram form in order to avoid obscuring the concepts of the present disclosure. Acronyms and other descriptive terminology may be used merely for convenience and clarity and are not intended to limit the scope of the disclosure.
Position determination techniques described herein may be implemented in conjunction with various wireless communication networks such as a wireless wide area network (WWAN), a wireless local area network (WLAN), a wireless personal area network (WPAN), and so on. The term “network” and “system” are often used interchangeably. A WWAN may be a Code Division Multiple Access (CDMA) network, a Time Division Multiple Access (TDMA) network, a Frequency Division Multiple Access (FDMA) network, an Orthogonal Frequency Division Multiple Access (OFDMA) network, a Single-Carrier Frequency Division Multiple Access (SC-FDMA) network, Long Term Evolution (LTE), and so on. A CDMA network may implement one or more radio access technologies (RATs) such as cdma2000, Wideband-CDMA (W-CDMA), and so on. Cdma2000 includes IS-95, IS-2000, and IS-856 standards. A TDMA network may implement Global System for Mobile Communications (GSM), Digital Advanced Mobile Phone System (D-AMPS), or some other RAT. GSM and W-CDMA are described in documents from a consortium named “3rd Generation Partnership Project” (3GPP). Cdma2000 is described in documents from a consortium named “3rd Generation Partnership Project 2” (3GPP2). 3GPP and 3GPP2 documents are publicly available. A WLAN may be an IEEE 802.11x network, and a WPAN may be a Bluetooth network, an IEEE 802.15x, or some other type of network. The techniques may also be implemented in conjunction with any combination of WWAN, WLAN and/or WPAN.
A satellite positioning system (SPS) typically includes a system of transmitters positioned to enable entities to determine their location on or above the Earth based, at least in part, on signals received from the transmitters. Such a transmitter typically transmits a signal marked with a repeating pseudo-random noise (PN) code of a set number of chips and may be located on ground based control stations, user equipment and/or space vehicles. In a particular example, such transmitters may be located on Earth orbiting satellite vehicles (SVs). For example, a SV in a constellation of Global Navigation Satellite System (GNSS) such as Global Positioning System (GPS), Galileo, GLONASS or Compass may transmit a signal marked with a PN code that is distinguishable from PN codes transmitted by other SVs in the constellation (e.g., using different PN codes for each satellite as in GPS or using the same code on different frequencies as in GLONASS). In accordance with certain aspects, the techniques presented herein are not restricted to global systems (e.g., GNSS) for SPS. For example, the techniques provided herein may be applied to or otherwise enabled for use in various regional systems, such as, e.g., Quasi-Zenith Satellite System (QZSS) over Japan, Indian Regional Navigational Satellite System (IRNSS) over India, Beidou over China, etc., and/or various augmentation systems (e.g., an Satellite Based Augmentation System (SBAS)) that may be associated with or otherwise enabled for use with one or more global and/or regional navigation satellite systems. By way of example but not limitation, an SBAS may include an augmentation system(s) that provides integrity information, differential corrections, etc., such as, e.g., Wide Area Augmentation System (WAAS), European Geostationary Navigation Overlay Service (EGNOS), Multi-functional Satellite Augmentation System (MSAS), GPS Aided Geo Augmented Navigation or GPS and Geo Augmented Navigation system (GAGAN), and/or the like. Thus, as used herein an SPS may include any combination of one or more global and/or regional navigation satellite systems and/or augmentation systems, and SPS signals may include SPS, SPS-like, and/or other signals associated with such one or more SPS.
As used herein, a mobile device, sometimes referred to as a mobile station (MS) or user equipment (UE), such as a cellular phone, mobile phone or other wireless communication device, personal communication system (PCS) device, personal navigation device (PND), Personal Information Manager (PIM), Personal Digital Assistant (PDA), laptop or other suitable mobile device which is capable of receiving wireless communication and/or navigation signals. The term “mobile device” is also intended to include devices which communicate with a personal navigation device (PND), such as by short-range wireless, infrared, wireline connection, or other connection—regardless of whether satellite signal reception, assistance data reception, and/or position-related processing occurs at the device or at the PND. Also, “mobile device” is intended to include all devices, including wireless communication devices, computers, laptops, etc. which are capable of communication with a server, such as via the Internet, WiFi, or other network, and regardless of whether satellite signal reception, assistance data reception, and/or position-related processing occurs at the device, at a server, or at another device associated with the network. Any operable combination of the above are also considered a “mobile device.”
In one particular implementation, a request for indoor navigation assistance data from a mobile device may specify an identifier, such as an LCI (location context identifier), to identify a specific area of a plurality of specific areas. The identity (ID) may be associated with a locally defined area such as, for example, a particular floor of a building or other indoor area that is not mapped according to a global coordinate system. In one example, upon entry of a specific area, a mobile device may request from a server, such as a location server, to provide area information covering just one specific area, or area information covering both the specific area and adjacent areas.
As shown in
Light-weight positioning uses a ranging model without map data. That is, only a list of APs and their respective locations and transmit powers are used to determine a range between a mobile device and each AP. In light-weight positioning, mapping data is not used by the mobile device in determining a position. Though light-weight positioning may be faster and require less bandwidth than traditional positioning, typical light-weight positioning may also have more uncertainty than traditional positioning.
Disclosed below is a novel specific area disambiguation solution based on light-weight positioning, for example, for precise indoor positioning (PIP), indoor navigation (InNav) or the like, that does not require communicating (transmitting and receiving) full map data when a server performs the method to select an area identifier. Alternatively, a mobile device performs the method to select an area identifier based on several maps from a server. Mobile device trajectories, each assuming a different specific area, are evaluated and then one is selected as the area identifier that a mobile device is currently traversing.
At 140, the server 120 prepares an ID, area information or a table of area information. The table area information includes, for each specific area, an identifier, a list of APs and a map of the specific area. The map, for each AP in the list of APs, may include a location of the AP and/or a transmit power level of the AP. The server 120 sends and the mobile device 110 receives a table of area information in response 150.
Measurements from available APs are recorded. The AP measurements (e.g., RSSI or RTT measurements) may be recording before, during and/or after the rough location request 130 and/or before, during and/or after the response 150. The AP measurements are group together based on which identifier each AP belongs. That is, based on which APs belong to a particular identifier (as found in the list of APs), a device groups AP measurements but exclude AP measurements not found in the particular list of APs.
At 160, the mobile device 110 computes a plurality of mobile device trajectories based on AP measurements from only the respective list of APs. That is, one trajectory corresponds to AP measurement from just one identifier and corresponding list of APs. Each trajectory assumes a specific area. Only AP measurements from APs belong to the specific area are used to determine each particular trajectory. The plurality of mobile device trajectories is passed to marker A. Marker A from the mobile device 110 and marker B from the server 120 continues on
The server 120 sends the area identifier in a response 330 to the mobile device 110.
At 830, the server 220 evaluates the various costs associated with each trajectory and selects an area identifier based on a lowest cost from the plurality of costs computed at 820. If two or more LCIs have equal costs associated with the respective LCI, in some embodiments, an area identifier is selected with a higher percentage of AP signals that are obtainable by the mobile device. For example, five received signals of a possible six APs for a first ID is selected over a second ID with six received signals of a possible eight APs. In other embodiments, an area identifier is selected with fewer APs received where two or more equal costs are computed. The area identifier with fewer received APs may be more accurate that an LCI with more but weaker APs. Still in other embodiments, when two or more equal lowest cost IDs are computed, a more common or popular area identifier is selected. At 840, the server 120 sends the area identifier to the mobile device 110. The method 800 ends at marker B′.
At 910, the mobile device 110 compares the plurality of mobile device trajectories to a reference. The reference may be a trajectory derived from sensor measurements, for example, from an inertial sensor. The reference may be a selection of a path by a user. For example, the user may input a path being used. Alternatively, the reference may be regularity of a trajectory. An ideal trajectory is composed of equally spaced location points. Alternatively, the reference may be a level of uncertainty. An ideal trajectory is composed of low uncertainty location points. Alternatively, the reference may be an expected power level from AP measurements. For example, while somewhere within a first LCI, a certain first AP gives received power measurements across the LCI of between −60 and −90 dBm and while somewhere within a second LCI, another certain second AP gives received power measurements between −70 and −95 dBm. If a received power level of the first AP is −100 dBm (10 dB below the first range) and a second received power level of a second AP is −80 dBm (within the second range), the second LCI is more likely because the received power level is within the second range. At 920, the mobile device 110 selects an area identifier based on the comparison of 910. Thread diagram 900 ends at marker A′ with the area identifier.
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Multiple factors may be weighed or considered when selecting a current area identifier. For example, a process may exclude area identifiers with unacceptable power levels (as shown in
When considering a user selection, uncertainty or an expected receive power measurement, a single location rather than a trajectory may be considered. A user may tell the mobile device 110 that the mobile device 110 is positioned at an established reference point, such as an intersection of adjoining paths, at a stairway, a doorway, or the like. The assumed area identifier that results in an estimated location closest to the established reference point may be selected as the current area identifier. Alternatively, when considering uncertainty, an assumed area identifier providing the lowest uncertainty for the point may be selected. Alternatively, when considering an expected receive power measurement to various APs, the area identifier having a power measurement from an AP or group of APs belonging to an area identifier that is closest to the area identifier range may be selected.
In
At 1820, a device receives, for a plurality of specific areas, area information, wherein for each specific area, the area information comprises an identifier, a list of access points (APs), and a map of the specific area. A receiver may be configured to receive the area information. The map, for each specific area, is optional. The identifier, for each of the plurality of specific areas, may be an LCI (location context identifier). The area information may further include a low-end of an expected power measurement for the list of APs. The device may also include a transmitter configured to send an assistance data request including the selected area identifier. The receiver may further be configured to receive an assistance data response based on the assistance data request. The receiver and transmitter may be combined into a transceiver. The receiver acts as a means for receiving and the transmitter acts as a means for transmitting and sending.
At 1830, a device provides a plurality of mobile device trajectories, wherein each trajectory of the plurality of mobile device trajectories corresponds to the list of APs from a hypothesized area. The plurality of mobile device trajectories may be a separate trajectory for each of the plurality of specific areas. That is, the mobile device 110 may compute a separate and unique trajectory itself for each specific area. Alternatively, the plurality of mobile device trajectories may be conglomerated into a single table. AP measurements from APs in the list of APs from the plurality of specific areas may reside in this single table. The AP measurements may be RSSI (received signal strength indication) measurements or RTT (round-trip time) measurements. The plurality of mobile device trajectories is based on the AP measurements.
Generally, the device may either be a mobile device 110 or a server 120. For example, a mobile device 110 may send an assistance data request, which includes a selected area identifier and receive an assistance data response based on the assistance data request. Alternatively, the method is performed in a server 120, where providing the plurality of mobile device trajectories means receiving, at the server 120 and from a mobile device 110, the plurality of mobile device trajectories and optionally sending, from the server 120 and to the mobile device 110, the selected area identifier or assistance data based on the selected identifier. When the device is a server 129, the receiver may be further configured to receive, from the mobile device 110, the plurality of mobile device trajectories.
At 1840, a device evaluates the plurality of mobile device trajectories. The device evaluating the plurality of mobile device trajectories may comparing each of the plurality of mobile device trajectories to a trajectory from inertial sensor measurements, or may check the plurality of mobile device trajectories for regularity.
At 1850, a device selects an area identifier bases on evaluating the plurality of mobile device trajectories. The device selecting an area identifier may include a user selection or may include selecting the area identifier bases on a minimum uncertainty of the plurality of mobile device trajectories. The device evaluating the plurality of mobile device trajectories may include comparing a received power level to the low-end of an expected power measurement. A processor coupled to the receiver may be configured to provide and evaluate the plurality of mobile device trajectories, and select the area identifier. When the device is a server 129, the processor is further configured to compare the plurality of mobile device trajectories to a reference to select the area identifier. The processor may act as a means for providing, evaluating and selecting.
A non-transient computer-readable storage medium, for a device to perform hypothesis localization, may include program code stored thereon, including program code to receive, provide, evaluate and select. When the device is a mobile device 110, the program code may further include program code to send an assistance data request including the selected area identifier, and receive an assistance data response based on the assistance data request. The program code to evaluate the plurality of mobile device trajectories may comprise program code to compare each of the plurality of mobile device trajectories to a trajectory from inertial sensor measurements. The program code to evaluate the plurality of mobile device trajectories may comprise program code to check the plurality of mobile device trajectories for regularity. The program code to select the area identifier may comprise program code to select the area identifier bases on a minimum uncertainty of the plurality of mobile device trajectories. The program code to evaluate the plurality of mobile device trajectories may comprise program code to compare a received power level to the low-end of an expected power measurement.
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The methodologies described herein may be implemented by various means depending upon the application. For example, these methodologies may be implemented in hardware, firmware, software, or any combination thereof. For a hardware implementation, the processing units may be implemented within one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, or a combination thereof.
For a firmware and/or software implementation, the methodologies may be implemented with modules (e.g., procedures, functions, and so on) that perform the functions described herein. Any machine-readable medium tangibly embodying instructions may be used in implementing the methodologies described herein. For example, software codes may be stored in a memory and executed by a processor unit. Memory may be implemented within the processor unit or external to the processor unit. As used herein the term “memory” refers to any type of long term, short term, volatile, nonvolatile, or other memory and is not to be limited to any particular type of memory or number of memories, or type of media upon which memory is stored.
If implemented in firmware and/or software, the functions may be stored as one or more instructions or code on a computer-readable medium. Examples include computer-readable media encoded with a data structure and computer-readable media encoded with a computer program. Computer-readable media includes physical computer storage media. A storage medium may be any available medium that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store desired program code in the form of instructions or data structures and that can be accessed by a computer; disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
In addition to storage on computer readable medium, instructions and/or data may be provided as signals on transmission media included in a communication apparatus. For example, a communication apparatus may include a transceiver having signals indicative of instructions and data. The instructions and data are configured to cause one or more processors to implement the functions outlined in the claims. That is, the communication apparatus includes transmission media with signals indicative of information to perform disclosed functions. At a first time, the transmission media included in the communication apparatus may include a first portion of the information to perform the disclosed functions, while at a second time the transmission media included in the communication apparatus may include a second portion of the information to perform the disclosed functions.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the spirit or scope of the disclosure.
