Patent Application
20130060514
1. Field of Disclosure
The present disclosure relates generally to motion event identification, and more specifically to detecting airliner motion events such as takeoff or landing.
2. Background
Airliner mobile telephone use is strictly regulated for a number of reasons: interference with sensitive aircraft navigation equipment, potential disruption of electronic aircraft flight control systems, cellular telephony channel reuse assumptions, and talking noise related nuisance to other passengers. There is a general consensus by airlines and government regulators that the risks associated with mobile telephony use on airliners outweigh the potential benefits.
It is therefore desirable to have a simple, accurate, robust, and power efficient mechanism for automatically disabling the mobile telephony features of personal electronic devices immediately after airliners become airborne, and for enabling the same telephony features upon landing.
Exemplary embodiments of the invention are directed to systems and methods for identifying mobile device motion events.
In some embodiments, a method is provided for identifying an airliner motion event at a mobile device. The method may comprise, for example: determining scalar acceleration signals from calibrated triaxial accelerometer data obtained from one or more accelerometers; filtering the scalar acceleration signals to reduce high frequency noise; processing the filtered scalar acceleration signals to generate an acceleration spread waveform; comparing the acceleration spread waveform to one or more predetermined patterns characteristic of an airliner motion event; and identifying an airliner motion event based on whether the comparing results in a substantial match.
In other embodiments, an apparatus is provided for identifying an airliner motion event at a mobile device. The apparatus may comprise, for example, one or more accelerometers, an acceleration feature extractor, and a motion event identification processor. The one or more accelerometers may be configured to output calibrated triaxial accelerometer data. The acceleration feature extractor may be configured to determine scalar acceleration signals from the calibrated triaxial accelerometer data, to filter the scalar acceleration signals to reduce high frequency noise, and to process the filtered scalar acceleration signals to generate an acceleration spread waveform. The motion event identification processor may be configured to compare the acceleration spread waveform to one or more predetermined patterns characteristic of an airliner motion event, and to identify an airliner motion event based on whether the comparing results in a substantial match.
In still other embodiments, another apparatus is provided for identifying an airliner motion event at a mobile device. The apparatus may comprise, for example: means for determining scalar acceleration signals from calibrated triaxial accelerometer data obtained from one or more accelerometers; means for filtering the scalar acceleration signals to reduce high frequency noise; means for processing the filtered scalar acceleration signals to generate an acceleration spread waveform; means for comparing the acceleration spread waveform to one or more predetermined patterns characteristic of an airliner motion event; and means for identifying an airliner motion event based on whether the comparing results in a substantial match.
In still other embodiments, a computer-readable medium comprising code is provided, which, when executed by a processor, causes the processor to perform operations for identifying an airliner motion event at a mobile device. The computer-readable medium may comprise, for example: code for determining scalar acceleration signals from calibrated triaxial accelerometer data obtained from one or more accelerometers; code for filtering the scalar acceleration signals to reduce high frequency noise; code for processing the filtered scalar acceleration signals to generate an acceleration spread waveform; code for comparing the acceleration spread waveform to one or more predetermined patterns characteristic of an airliner motion event; and code for identifying an airliner motion event based on whether the comparing results in a substantial match.
In still other embodiments, another apparatus is provided for identifying an airliner motion event at a mobile device. The apparatus may comprise, for example, one or more processors and memory coupled to the one or more processors. The one or more processors may be configured to: determine scalar acceleration signals from calibrated triaxial accelerometer data obtained from one or more accelerometers, filter the scalar acceleration signals to reduce high frequency noise, process the filtered scalar acceleration signals to generate an acceleration spread waveform, compare the acceleration spread waveform to one or more predetermined patterns characteristic of an airliner motion event, and identify an airliner motion event based on whether the comparing results in a substantial match. The memory may be configured to store related data and/or instructions.
The accompanying drawings are presented to aid in the description of embodiments of the invention and are provided solely for illustration of the embodiments and not limitation thereof.
Aspects of the invention are disclosed in the following description and related drawings directed to specific embodiments of the invention. Alternate embodiments may be devised without departing from the scope of the invention. Additionally, well-known elements of the invention will not be described in detail or will be omitted so as not to obscure the relevant details of the invention.
The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any embodiment described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other embodiments. Likewise, the term “embodiments of the invention” does not require that all embodiments of the invention include the discussed feature, advantage or mode of operation.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of embodiments of the invention. As used herein, the singular forms “a,” “an,” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes,” and/or “including,” when used herein, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
Further, many embodiments are described in terms of sequences of actions to be performed by, for example, elements of a computing device. It will be recognized that various actions described herein can be performed by specific circuits (e.g., application specific integrated circuits (ASICs)), by program instructions being executed by one or more processors, or by a combination of both. Additionally, the sequence of actions described herein can be considered to be embodied entirely within any form of computer readable storage medium having stored therein a corresponding set of computer instructions that upon execution would cause an associated processor to perform the functionality described herein. Thus, the various aspects of the invention may be embodied in a number of different forms, all of which have been contemplated to be within the scope of the claimed subject matter. In addition, for each of the embodiments described herein, the corresponding form of any such embodiments may be described herein as, for example, “logic configured to” perform the described action.
As discussed in the Background above, it is desirable to have a simple, accurate, robust, and power efficient mechanism for automatically controlling the mobile telephony features of personal electronic devices when present on airliners. Accordingly, systems and methods are provided herein for detecting airliner motion events such as takeoff and/or landing using scalar acceleration waveform analysis (e.g., derived from triaxial accelerometer data), and for controlling mobile devices based on these events. Although scalar acceleration takeoff and landing signal levels may be relatively small compared to the always-present gravity of earth, scalar acceleration signals can be filtered for takeoff and landing detection at low bandwidth, reducing noise to acceptable levels.
The accelerometer 110 is typically a triaxial accelerometer that provides acceleration data for three different axes. Other examples may include multiple (e.g., three) single axis accelerometers. Further, it will be appreciated that other devices from which acceleration may be derived can be used, so the embodiments should not be construed to be limited to the specific devices discussed explicitly herein.
The acceleration feature extractor 106 monitors the acceleration signals from the accelerometer 110 and performs various processing to characterize acceleration. The acceleration feature extractor 106 may characterize acceleration in a variety of ways, but the characterization typically includes determining a calibrated scalar acceleration signal from the vector acceleration signals (e.g., from triaxial accelerometer data), generating a moving average of the scalar acceleration data over a given averaging period (e.g., a Scalar Acceleration Averaging Period) to filter out high frequency noise, and computing an acceleration spread over a given observation window (e.g., an Acceleration Spread Observation Window Period). Acceleration spread corresponds to the difference between the maximum and the minimum scalar acceleration values in the observation window. The accelerometer 110 may be calibrated, for example, to the extent that any modification of device orientation generates less than a one percent change in acceleration spread. For some applications, it has been found that a Scalar Acceleration Averaging Period on the order of ten seconds (e.g., about twelve seconds, or anywhere in the range of about one and about sixty seconds) and an Acceleration Spread Observation Window Period on the order of a minute or so (e.g., about sixty seconds, or anywhere in the range of about ten and about one hundred and eighty seconds) provide acceleration spread waveforms that yield good results for airliner motion event identification. It will be appreciated, however, that other moving average periods and observation windows may be used as desired, depending on the particular application.
The acceleration feature extractor 106 outputs the extracted acceleration feature information (e.g., an acceleration spread waveform), and provides this information to the motion event identification processor 102. The motion event identification processor 102 is accordingly configured to determine whether the extracted acceleration features correspond to the takeoff or landing of an airliner, such as by employing various pattern matching techniques to recognize acceleration spread events, or a combination thereof, that are unique to airliner takeoffs and landings, as distinguished from other motion events (e.g., pedestrial stepping, automobile acceleration, etc.).
In general, acceleration spread events may be “positive” or “negative,” depending on the sign of the acceleration spread during the event. For example, the acceleration spread may be deemed positive if the observation window minimum occurs before the maximum, and negative otherwise.
The motion event identification processor 102 may implement various algorithms to identify airliner motion events such as takeoff and landing based on the detection of one or more acceleration spread events, including basic as well as enhanced identification algorithms. For example, basic detection algorithms may look for the acceleration patterns characteristic of airliner takeoff ground run and climb events or landing ground run events and their associated quiescent periods. Enhanced algorithms may further require a certain number of “flight events” to be detected within a specified period prior to landing events and subsequent to takeoff events.
For some applications, it has been found that a Takeoff Ground Run and Climb Event Period on the order of tens of seconds (e.g., a TMin of about 30 seconds and a TMax of about 100 seconds) used in conjunction with a Minimum Takeoff Ground Run and Climb Event Amplitude on the order of a tenth of the acceleration due to gravity (e.g., an AMin of about 0.075 go) yields appropriate airliner takeoff ground run and climb event detection results. It will be appreciated; however, that other takeoff ground run and climb event periods and/or minimum amplitudes may be used as desired, depending on the particular application.
The motion event identification processor 102 may accordingly identify an airliner takeoff event when it detects a takeoff ground run and climb event acceleration spread pattern. However, airliner takeoff ground run and climb events typically follow a quiescent period, corresponding to periods of relatively little scalar acceleration change as the airliner is taxied to the end of the runway prior to takeoff and subsequently waits for permission to begin the takeoff ground run. Accordingly, in some designs, the motion event identification processor 102 may identify an airliner takeoff event when it detects a takeoff ground run and climb event acceleration spread pattern that follows a quiescent period of minimum duration as shown in
For some applications, it has been found that a Landing Positive Ground Run Event Period on the order of several tens of seconds (e.g., a T+Min of about 35 seconds and a T+Max of about 85 seconds) used in conjunction with a Landing Positive Ground Run Event Amplitude Range on the order of a few to several hundredths of the acceleration due to gravity (e.g., an A+Min of about 0.036 go and an A+Max of about 0.070 go), and a Landing Negative Ground Run Event Period on the order of tens of seconds to a few minutes (e.g., a T−Min of about 35 seconds and a T−Max of about 120 seconds) used in conjunction with a Landing Negative Ground Run Event Amplitude Range on the order of a few to several hundredths of the acceleration due to gravity (e.g., an A−Min of about −0.036 go and an A−Max of about −0.070 go), yield appropriate airliner landing ground run detection results. It will be appreciated, however, that other landing ground run event periods and/or amplitude ranges may be used as desired, depending on the particular application.
The motion event identification processor 102 may accordingly identify an airliner landing event when it detects a landing ground run event acceleration spread pattern. However, airliner landing ground run events are typically followed by a quiescent period, corresponding to periods of relatively little scalar acceleration change as the airliner is taxied from the runway to its gate and waits to be prepared for passengers to unload. Accordingly, in some designs, the motion event identification processor 102 may identify an airliner landing event when it detects a landing ground run event acceleration spread pattern that is followed by a quiescent period of minimum duration as shown in
As discussed above, enhanced algorithms may further include the detection and use of certain flight events to verify the integrity of any otherwise identified airliner motion events. Such flight events may be detected, for example, from acceleration spread patterns associated with low frequency, large amplitude scalar acceleration changes typical of in-flight environments where the airliner's acceleration vector is generally aligned with that of gravity.
For some applications, it has been found that a Positive Flight Event Period on the order of tens of seconds to a few minutes (e.g., a T+Min of about 15 seconds and a T+Max of about 150 seconds) used in conjunction with a Positive Flight Event Amplitude Range on the order of a few tenths of the acceleration due to gravity (e.g., an A+Min of about 0.045 go and an A+Max of about 0.300 go), and a Negative Flight Event Period on the order of tens of seconds to a few minutes (e.g., a T−Min of about 15 seconds and a T−Max of about 150 seconds) used in conjunction with a Negative Flight Event Amplitude Range on the order of a few tenths of the acceleration due to gravity (e.g., an A−Min of about −0.045 go and an A−Max of about −0.300 go), yield appropriate airliner flight detection results. It will be appreciated, however, that other flight event periods and/or amplitude ranges may be used as desired, depending on the particular application.
The motion event identification processor 102 may accordingly identify an airliner flight event when it detects a flight event acceleration spread pattern such as the one illustrated in
For example, the motion event identification processor 102 may refrain from declaring an airliner takeoff event based on what would otherwise appear to be one unless it is followed by a Minimum Number of Takeoff Flight Events (NFET) over a Maximum Takeoff Flight Event Period (TFET) following the takeoff ground run and climb acceleration spread pattern event. Similarly, the motion event identification processor 102 may refrain from declaring an airliner landing event based on what would otherwise appear to be one unless it is preceded by a Minimum Number of Landing Flight Events (NFEL) over a Maximum Landing Flight Event Period (TFEL) before the landing acceleration spread pattern event. For some applications, it has been found that a Minimum Number of Takeoff Flight Events on the order of one to several (e.g., an NFET of about 2) in conjunction with a Maximum Takeoff Flight Event Period on the order of a few minutes (e.g., a TFET of about 300 seconds), and a Minimum Number of Landing Flight Events on the order of one to several (e.g., an NFEL of about 2) in conjunction with a Maximum Landing Flight Event Period on the order of several minutes (e.g., a TFEL of about 480 seconds), provide sufficient certainty as to whether a given airliner takeoff ground run and climb event or landing ground run event, and their associated quiescent periods, does in fact correspond to an airliner motion event. It will be appreciated, however, that other flight event counts and periods may be used as desired, depending on the particular application.
The identification of airliner motion events such as takeoff and landing may be useful in a variety of post-identification activities. For example, airliner motion event identification may be used to facilitate automatically disabling the mobile telephony features of a mobile device onboard the airliner (e.g., when the mobile device is in the user's front seat pocket, carry-on luggage, stowed baggage, etc.). This is often referred to as entering “airplane mode,” whereby the user is allowed to listen to music, play a game, or review stored email messages, for example, but is prevented from making phone calls, use Bluetooth accessories, etc. Usually, only mobile station wireless communication features are rendered inoperative in airplane mode. Accordingly, the motion event identification processor 102 may be further configured to cause a corresponding mobile device (not shown) to enter airplane mode or the like during flight (e.g., after identification of an airliner takeoff event) and/or to exit airplane mode or the like following completion of the flight (e.g., after identification of an airliner landing event).
In addition, the motion event identification processor 102 may be further configured to provide, to the user or another device, certain contextual information or other services related to travel in a commercial airliner. For example, the motion event identification processor 102 may be further configured to cause a corresponding mobile device (not shown) to display flight progress or timing information, to automatically disable speakerphone functionality, or to provide updated connecting flight information.
As shown, accelerometer measurement error may be initially determined and calibrated to required standards to ensure that inferred scalar acceleration is orientation independent to an appropriate degree (block 704). For example, the one or more accelerometers may be calibrated to the extent that any modification of device orientation generates less than a one percent change in acceleration spread. Calibrated triaxial acceleration data is then obtained, at a particular sampling frequency, and the scalar acceleration signal is computed (block 708). The scalar acceleration signal may be filtered at low bandwidth to reduce noise (block 712), and the acceleration spread waveform may be generated for an optimized window period (block 716).
The acceleration spread waveform may then be compared to one or more predetermined patterns characteristic of an airliner motion event (block 720), and in some embodiments, to one or more predetermined patterns characteristic of an airliner flight event (block 724), as discussed above. An airliner motion event may then be identified (decision 728) as a takeoff event when the comparing results in a substantial match with a takeoff pattern (block 732), or a landing event when the comparing results in a substantial match with a landing pattern (block 736). If no match is found, operation may return to determining the scalar acceleration signal over a subsequent time window (block 708). In some embodiments, where flight events are taken into account, the identification of the airliner motion event may be further based on whether a minimum number of flight events are detected over a given time period.
As discussed in more detail above, the one or more predetermined patterns may include an acceleration spread pattern having a quiescent period followed by an airliner takeoff ground run and climb event. The airliner takeoff ground run and climb event may be defined, for example, by a positive acceleration spread having an amplitude above a specified threshold for a time period within a specified range. The one or more predetermined patterns may also include an acceleration spread pattern having a landing ground run event followed by a quiescent period. The landing ground run event may be defined, for example, by a positive acceleration spread having an amplitude within a specified range for a time period within a specified range, and a negative acceleration spread, adjacent in time to the positive acceleration spread, having an amplitude within a specified range for a time period within a specified range.
The use of the acceleration spread in the manner described above advantageously provides for an efficient identification of airliner motion events, such as airliner takeoff and landing events. In some embodiments, the airliner motion event identification may be used to enable or disable at least one telephony function of the mobile device (block 740).
On the receive path, antennas 834 may receive signals transmitted by mobile accessory devices 802 (e.g., Bluetooth), various access points 804 (e.g., WLAN) or 806 (e.g., WWAN), Global Navigation Satellite Systems (GNSS) 808 (e.g., GPS), etc. A receiver (RCVR) 836 may then condition (e.g., filter, amplify, downconvert, and digitize) a received signal from the one or more antennas 834 and provide samples. A demodulator (Demod) 826 may process (e.g., descramble, channelize, and demodulate) the samples and provide symbol estimates. A decoder 828 may further process (e.g., deinterleave and decode) the symbol estimates and provide decoded data. Encoder 822, modulator 824, demodulator 826, and decoder 828 may comprise a modem processor 820. These units may perform processing in accordance with the radio technology or technologies used for communication.
According to one or more embodiments, the wireless communication device 800 may further include a motion event identification device 850 of the type described above, such as the motion event identification device 100 shown in
Those of skill in the art will appreciate that information and signals may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits, symbols, and chips that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.
Further, those of skill in the art will appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The methods, sequences and/or algorithms described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such that the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor.
Accordingly, an embodiment of the invention can include a computer readable media embodying a method for identifying an airliner takeoff or landing event at a mobile device using triaxial accelerometer data. Accordingly, the invention is not limited to illustrated examples and any means for performing the functionality described herein are included in embodiments of the invention.
While the foregoing disclosure shows illustrative embodiments of the invention, it should be noted that various changes and modifications could be made herein without departing from the scope of the invention as defined by the appended claims. The functions, steps and/or actions of the method claims in accordance with the embodiments of the invention described herein need not be performed in any particular order. Furthermore, although elements of the invention may be described or claimed in the singular, the plural is contemplated unless limitation to the singular is explicitly stated.
The present application for patent claims priority to Provisional Application No. 61/530,328 entitled “MEMS ACCELEROMETER AIRLINER TAKEOFF AND LANDING DETECTION” filed Sep. 1, 2011, assigned to the assignee hereof and hereby expressly incorporated by reference herein.
| Number | Date | Country | |
|---|---|---|---|
| 61530328 | Sep 2011 | US |
