Providing Universal Location Services
`Using a Wireless E911 Location Network
`
`James M. Zagami and Steen A. Parl, Signatron Technology Corporation
`Julian J. Bussgang, Consultant
`Karen Devereaux Melillo, University of Massachusetts Lowell
`
`ABSTRACT
`
`This article reviews the issues associated with the development
`of an E911 location network in light of the desire to leverage
`the E911 location network to provide universal non-cellular location-based services. The
`key issues are illustrated with a system originally developed for locating elderly patients
`with Alzheimer’s disease.
`
`I
`
`n June 1996, the FCC adopted FCC Docket 94-102
`[1] as an official report and order (R&O), thereby
`officially mandating that wireless 911 callers receive the same
`level of emergency service as that available to wireline callers
`who have benefited from wireline Enhanced 911 (E911). One of
`the key provisions of FCC 94-102 is that cellular, personal com-
`munications services (PCS), and specialized mobile radio (SMR)
`service providers deploy a means of automatically locating 911
`callers to within 125 m in 67 percent of all measurements by
`October 31, 2001. In the process, the FCC R&O will create what
`is forecast to be a multibillion-dollar market for caller location
`technologies [2], which in turn is expected to catalyze the offering
`of a new array of noncellular location-based services such as
`monitoring the location of people, cargo, or vehicles.
`In this article we review the issues associated with E911 loca-
`tion services and discuss how a system originally developed by
`Signatron Technology Corporation (STC) for locating lost
`patients may offer performance and cost advantages for an E911
`location implementation, particularly when the location base sta-
`tion equipment is used to provide both E911 and general location
`services.
`We begin with a brief overview of the requirements of a cellu-
`lar E911 location system and an overview of existing location
`technologies. We then give an overview of the Signatron Location
`System (SLS) developed by STC, and conclude with two examples
`describing how this technology may be applied to locating wan-
`dering Alzheimer’s disease patients and tracking parolees.
`
`E911 LOCATION NETWORK REQUIREMENTS
`Cellular telephone systems are all similar in their basic architec-
`ture. A network of radio base stations that handles multiple
`callers is controlled by a network of mobile switching centers
`(MSCs) which are linked via the public telephone network. A typ-
`ical example is shown in Fig. 1. The home location register
`(HLR) and vistor location register (VLR) databases maintained
`at the MSC are used to validate mobile units, locate roaming
`units, and provide billing records for the central office. While the
`general architecture of cellular phone networks is similar, the air
`interfaces differ greatly among cellular standards. In the United
`States, the most common air interface in use is still the Advanced
`Mobile Phone System (AMPS), but new digital transmission tech-
`nologies are expected to supplant the AMPS standard over the
`next decade. The most common digital cellular/PCS technologies
`are code-division multiple access, or CDMA (EIA/TIA IS-95),
`time-division multiple access, or TDMA (EIA/TIA IS-136, sup-
`
`planting IS-54), and the European-developed
`Global System for Mobile Communications
`(GSM). Each of these standards uses different
`transmitted waveforms and control channel
`data formats, both of which will generally impact the location sys-
`tem design. As digital systems become operational, a major issue
`will be the operation of location systems at digital/analog system
`boundaries where the handset may be in digital mode, and the
`location measurement may involve the use of both analog and
`digital receiver sites which may even be in different frequency
`bands; such operation requires careful design of measurement
`equipment and coordination among location receivers.
`Location technologies that have been proposed to date to
`meet FCC 94-102 fall into two broad categories: network-based
`solutions and handset-based solutions.
`Proposed network based location systems are generally either
`independent overlay systems or technologies designed to be inte-
`grated into base stations to measure certain signal characteristics,
`such as time of arrival (TOA) or angle of arrival (AOA) of the
`desired transmitted signal as received at several receiver stations
`from which a location is estimated; there are no modifications to
`the mobile handsets.
`Handset-based techniques rely on a modified handset to calcu-
`late its own position. One such technique is to use a Global Posi-
`tioning System (GPS) receiver embedded in the handset. In
`addition to self-location, these techniques also require a return
`data path to report the location to the network for relay to the
`emergency operator. The obvious drawbacks of handset-based
`approaches are the cost of developing a suitable low-power and
`economical integrated technology for use in the handsets and the
`cost of deploying new handsets. Because of the drawbacks of non-
`network technologies, cellular carriers generally favor the use of a
`network-based approach, provided the necessary infrastructure is
`not prohibitively expensive.
`A network-based location overlay system can be implemented
`by deploying location receiver/processors at either existing base
`stations or new receiver sites. These location receiver/processors
`are used to capture signals from the desired mobile unit and to
`transmit either the captured digitized signal or certain signal
`attributes such as AOA to a computer for location estimation.
`Preferably, the location receivers will be located at existing base
`station sites and will use the existing cellular antennas and RF
`front-end circuitry. There are, however, a number of technical
`hurdles relating to the level of integration or interaction the loca-
`tion system requires with the existing cellular base stations or
`switches. In particular, the location system would ideally interface
`to the existing base stations such that the base station controller
`can invoke the location system when a 911 call is placed and
`inform the location system which channel the 911 call has been
`assigned. In general, a single such interface to base stations pro-
`
`66
`
`0163-6804/98/$10.00 © 1998 IEEE
`
`IEEE Communications Magazine • April 1998
`
`Apple, Inc. Exhibit 1007 Page 1
`
`

`
`Mobile cellular system
`
`BS
`
`BS
`
`BS
`
`BS
`
`BS
`
`Fixed network
`
`Mobile/fixed
`network
`interface
`
`HLR
`
`MSC
`
`PSTN
`
`VLR
`
`BS: Base station
`MSC: Mobile switching center
`PSTN: Public switched telephone network
`HLR: Home location register
`VLR: Visitor location register
`
`n Figure 1. Cellular radio network configuration.
`
`duced by many different manufacturers is not possible,
`especially for already deployed AMPS systems. The loca-
`tion system must therefore include a means of monitoring
`the control channel traffic to detect 911 calls and to
`decode the subsequently assigned voice channels for loca-
`tion tracking. It is anticipated that digital base station
`equipment manufacturers will eventually integrate loca-
`tion technology into base stations or provide an interface
`to the control channel information for selected location
`systems.
`After the location system locates the E911 mobile unit,
`the location and phone ID must be relayed to the Public
`Service Answering Point (PSAP) for display and use by
`the emergency operator or for automated dispatch of
`response personnel. This issue is being addressed by the
`National Emergency Number Association (NENA) in the
`form of a standard data format for reporting Automatic Location
`Identification (ALI) data and should be followed by prospective
`E911 ALI equipment vendors.
`In short, we summarize the desired features of a cellular E911
`ALI system as follows:
`• Meet FCC 94-102 (<125 m accuracy for 67 percent of mea-
`surements).
`• Coverage at least comparable to the cellular system.
`• Seamless integration with existing base stations, no modifica-
`tions to nor interaction with existing base station equipment,
`other than gaining access to the necessary antenna signals.
`However, some interaction may be required to identify 911
`calls in encrypted digital systems.
`• Minimal data rate backhaul requirements, minimizing recur-
`ring charges.
`• Low-cost location receiver equipment.
`• Use existing cellular antennas and shelters where possible to
`avoid added recurring operation costs.
`• Reliable operation.
`• Expandable for increased future capacity.
`• Support for other location services with no impact on cellu-
`lar capacity nor interaction with cellular systems.
`• Capable of interfacing to E911 terrestrial networks for ALI
`reporting.
`Of course, some approaches may sacrifice one or more of
`these criteria in order to gain an advantage in another. For
`instance, AOA approaches generally propose using additional or
`custom antennas, sacrificing added recurring costs in return for
`better performance. TDOA approaches can use the existing cellu-
`lar antennas, but generally require a high-data-rate backhaul. The
`SLS approach discussed below draws from the benefits of both
`approaches; the result is that the existing cellular antennas can be
`used without the need for costly high-speed data backhauls.
`
`tagged, and transmitted to a central processor for cross-correlation
`and position estimation using hyperbolic intersection. Because of
`system inaccuracies and differences in propagation channels to
`each of the base stations, the hyperbolae generally will not inter-
`sect at the actual location. Also, two hyperbolae can intersect at
`two points, creating ambiguities. The main drawback of TDOA is
`that a large bandwidth is required to transmit the captured digitized
`waveform to a central site. This is not only costly, but will also limit
`the capability of such a system to serve high-capacity commercial
`location applications. To overcome this, some systems use TOA,
`where the TOAs of a known signal are estimated directly at each
`base station. Another concern for TOA/TDOA methods is that,
`in rural areas, cellular base stations are widely spaced and often
`the minimum required three base stations cannot all receive the
`desired signal. In such areas, additional TDOA location receivers
`may have to be sited to provide adequate coverage.
`AOA systems use antenna arrays consisting of two or more
`elements which are used to measure the line of bearing as seen
`at two or more base stations. The location is estimated by trian-
`gulation, using a best fit approximation of the intersection of the
`lines of bearing, or by other methods that try to improve the
`accuracy of the estimate. The accuracy improves with the size of
`the array, which implies using either a large number of elements
`or, in order to lower costs, a large interelement spacing. Since
`wider antenna spacing introduces ambiguities in the results, the
`existing cellular diversity antennas cannot be used in traditional
`AOA location systems. Also, AOA systems generally discard
`other useful signal information, such as amplitude, and thus
`result in less than optimum accuracy. AOA processing can be
`less costly than TDOA processing, but the savings in processing
`cost are generally offset by the fixed and recurring costs of plac-
`ing custom antenna arrays on an antenna structure for proper
`operation. AOA systems are particularly susceptible to strong
`angular multipath degradation and also exhibit very poor perfor-
`mance in rural areas where the linear orientation of base stations
`along major roads causes geometric dilution of precision
`(GDOP). The SLS approach is less sensitive to GDOP than
`either AOA or TDOA alone, since it incorporates AOA and
`TDOA in position estimation.
`A comparison of various location technologies, including
`the new STC SLS system discussed below, is given in Table 1.
`
`THE SLS APPROACH AND ITS APPLICATIONS
`A number of location technologies are being designed specifically
`to locate cellular telephones, and some of these technologies may
`later be adapted to provide additional location services. STC on
`the other hand, has developed the SLS, a low-cost low-power
`approach designed specifically for locating or tracking people and
`objects outfitted with a very-low-cost radio transceiver. The tech-
`nology relies on a maximum likelihood estimate (MLE) of loca-
`
`OVERVIEW OF
`POSITION LOCATION TECHNIQUES
`The two most widely known network-based location technologies
`used in proposed mobile phone location systems are TDOA and
`AOA. TDOA systems use the principle that the emitter location
`can be estimated by intersection of the hyperbolae of constant
`differential TOAs of the signal at two or more pairs of base sta-
`tions. AOA systems use simple triangulation based on estimated
`AOA of a signal at two or more base stations to estimate the
`location of a desired transmitter. Variations of both of these
`approaches have been proposed for cellular location and are dis-
`cussed in [3]. Below we discuss key characteristics relevant to
`both cellular phone and noncellular applications.
`Conventional TDOA technologies require that the desired sig-
`nal be captured and digitized at three or more base stations, time-
`
`IEEE Communications Magazine • April 1998
`
`67
`
`Apple, Inc. Exhibit 1007 Page 2
`
`

`
`tion to achieve higher accuracy than the conventional
`TOA/TDOA and AOA methods described above. This new SLS
`technique (patent pending) is also being applied to develop a
`product that promises to economically meet E911 requirements
`so that the same network can be used for a range of low-cost
`high-capacity location-based services. The SLS processes the
`wireless signal in such a way that both the direction and differen-
`tial range of the mobile unit relative to the base stations are
`taken into account, but without incurring the information loss of
`
`the traditional intermediate step of estimating direction angles or
`time delays.
`By utilizing a known signal structure and intelligent assign-
`ment of unused cellular channels, the SLS can use existing cellu-
`lar antennas to simultaneously support both E911 and noncellular
`applications, such as the lost patient location application dis-
`cussed below.
`A major benefit of the STC SLS is that the AOA ambiguity
`associated with using the large diversity antenna spacing at cellu-
`lar base stations is eliminated by using the implicit
`TDOA information without adding custom antennas.
`Another major benefit is that only very little informa-
`tion need be transmitted to a central site. As an illustra-
`tion of the former benefit, Fig. 2a shows the likelihood
`function expected using AOA information only, illus-
`trating how high accuracy unfortunately also means
`high ambiguity when only two widely spaced antenna
`elements are used. Figure 2b shows that SLS, by incor-
`porating TDOA information, achieves both a low loca-
`tion error (narrow peak of the likelihood function) and
`low ambiguity (single peak). These typical examples
`were computer-generated assuming a 100 mW mobile
`transmitter and four base stations forming a square with
`5 mi sides. As with any method, there is a finite proba-
`bility that noise can cause a smaller peak to be erro-
`neously chosen. However, such an error can usually be
`detected by correlating with previous results or request-
`ing a new measurement.
`The approach to multipath is twofold: take into
`account amplitude information, and use more than the
`minimum number of base station measurements. This
`approach, while not optimal, is a cost-effective means to
`meet FCC E911 requirements. Simulations have demon-
`strated the SLS method to be relatively insensitive to
`multipath, and laboratory simulator tests and field tests
`are planned to verify these results.
`We are currently studying the performance of the
`SLS in rural areas where the geometry of base stations
`is likely to impair performance. Thus far, computer sim-
`ulations indicate that SLS performance will exceed that
`of traditional AOA or TDOA approaches in such areas,
`providing approximately 75 m root mean square (rms)
`error.
`
`5
`
`4
`
`3
`
`y (mi)
`
`2
`
`1
`
`1
`
`2
`
`x (mi)
`
`3
`
`4
`
`0
`
`5
`
`1
`
`0.9
`
`0.8
`
`0.7
`
`0.6
`
`0.5
`
`0.4
`
`0.3
`
`0.2
`
`0.1
`
`0
`
`0
`
`a
`
`1
`
`0.8
`
`0.6
`
`0.4
`
`0.2
`
`0
`
`–0.2
`
`0
`
`b
`
`5
`
`4
`
`3
`
`2
`
`y (mi)
`
`1
`
`1
`
`x (mi)
`
`2
`
`3
`
`4
`
`0
`
`5
`
`n Figure 2. a) A high accuracy likelihood function showing narrow location
`peaks but many ambiguous locations (e.g., using AOA with a large element
`spacing); b) the SLS combines high-accuracy high-ambiguity implicit AOA
`data with low-ambiguity lower-accuracy implicit TDOA data to get the best of
`both: high accuracy and low ambiguity.
`
`NONCELLULAR APPLICATIONS OF THE SLS
`If an infrastructure deployed to locate cellular phones
`is to provide additional revenue-generating location
`services, the requirements of these “other” services
`must be well understood by the equipment and net-
`work developers. It is critical, therefore, that wireless
`E911 location technologies and systems take into
`account the requirements of non-911 services. Cellular
`carriers must thus focus on deploying a satisfactory
`and economical solution that combines compliance
`with FCC 94-102 with support of these other location
`services. For example, a location system designed to
`locate a cellular telephone waveform and operate in
`the cellular network may not necessarily be the best
`solution for providing the high capacity, wide cover-
`age, accuracy, low cost, and long battery life that will
`be demanded by many noncellular location service
`applications.
`SLS addresses the fundamental problem of location
`monitoring, which is defined as the remote radio loca-
`tion of the position of a mobile transmitter. The person
`or object to be located or tracked carries a very small
`
`68
`
`IEEE Communications Magazine • April 1998
`
`Apple, Inc. Exhibit 1007 Page 3
`
`

`
`Method Base station cost
`
`Coverage
`
`Backhaul requirement
`
`Handset
`
`GPS
`
`Low
`
`AOA
`
`High: cannot use
`cellular base station
`antennas
`
`TOA
`
`High
`
`TDOA
`
`High
`
`STC SLS Low
`
`Poor in urban areas Low: only location
`estimate is forwarded
`
`Requires data
`link
`
`Cellular handset
`modification
`
`Good
`
`Good
`
`Good
`
`Good
`
`Low: only measured
`angles are sent to a
`central facility
`
`Low
`
`None
`
`None
`
`High: sampled data trans- None
`mitted to a central facility
`
`Low
`
`None
`
`n Table 1. Comparison of location technologies.
`
`and inexpensive low-power unit, which on
`command transmits a signal generated by
`very simple low-cost electronics. The signal
`is received at several base stations, and the
`location estimate is found by using a maxi-
`mum likelihood algorithm, incorporating
`TDOA and AOA as special cases. In all
`but a few degenerate cases, only two base
`stations can suffice. A very inexpensive
`low-power single integrated circuit (IC)
`will enable low-cost location devices with
`many applications, as shown in Fig. 3. The
`use of a single IC location tag is made pos-
`sible by the simple signal structure at the
`core of the concept. Initially, only services
`that present either a significant increase in
`safety or a significant cost advantage over
`hospitalization or confinement alternatives
`will likely find widespread application. Two examples of important
`applications are addressed below. As volume drives down per-unit
`costs, however, other applications such as pet location or routine
`cargo tracking will become economically feasible.
`
`LOCATING LOST PATIENTS WITH
`ALZHEIMER’S DISEASE
`All too often, newspapers report that someone with cognitive
`impairment has gotten lost and perished. There is a pressing need
`for the ability to quickly locate patients who have wandered off
`and become lost. In order to find the patient quickly, an accuracy
`of at least 100 ft is desired.
`
`Bracelet:
`Alzheimer’s patients
`Elderly persons
`Children
`
`Pager:
`Mail carriers
`Service personnel
`Couriers
`Law enforcement officers
`
`Ankle bracelet:
`Criminal justice
`applications
`
`Digital cellular/PCS
`mobile phones:
`
`Signatron
`Technology
`
`Clip-on tag:
`Pets
`
`Adhesive-backed single-use
`location tag:
`Cargo tracking
`
`Externally powered
`location unit:
`Fleet tracking
`Stolen car recovery
`Auto repossession
`
`n Figure 3. Low-cost low-power location unit.
`
`The most common disease that can cause cognitive impair-
`ment and geriatric wandering is Alzheimer’s disease. There is as
`yet no definitive diagnostic test in use and no cure for this dis-
`ease, although much promising research is in progress. The dis-
`ease is progressive, and patients experience increasing and
`irreversible levels of confusion, memory loss, personality change,
`behavior change, and impaired judgment. Patients inevitably lose
`orientation, and have difficulty remembering directions.
`Data regarding the percentage of institutionalized dementia
`patients who wander range from 11 to 24 percent. In community-
`dwelling patients, studies have reported wandering in up to 59
`percent of afflicted individuals. The goal of location management
`for wandering is not to totally confine the patients, because it is
`considered desirable to give patients both a sense of indepen-
`dence and the opportunity to exercise. Rather, the
`goal is to ensure the safety of the wandering individu-
`al, and to lessen the caregiver burden [4, 5].
`Statistics indicate that currently over 4 million
`Americans suffer from Alzheimer’s disease. In 1989, it
`was estimated that over 10 percent of people over 65
`were afflicted with the disease [6]. It has been estimat-
`ed that nearly half (47 percent) of people aged 85 and
`older are afflicted with the disease [6]. With the pro-
`gressive increase in the average age of the U.S. popu-
`lation, the number of Alzheimer’s patients is predicted
`to increase at a rate of 10 percent/year. At such a
`rate, 14 million Americans are expected to have the
`disease by the mid-21st century, unless a cure or
`means of prevention is found.
`In the United States, over 75 percent of
`Alzheimer’s patients, or over 3 million persons, live at
`home, in noninstitutional open surroundings. Most
`frequently, they are elderly but otherwise in good
`health and fully ambulant. Thus, they are very capable
`of wandering off. When they do, and it happens often,
`they are frequently unable to find their way back
`home. The situation is fraught with danger for the
`patients and causes considerable stress to a caregiver,
`often their spouse, who in general is also elderly.
`At the present time, the only provision for such
`patients is a simple patient ID bracelet engraved with
`the patient’s identity data, often including a number
`registered in a central registry. Such devices, while
`helpful, are very rudimentary, and rely on the patient
`being intercepted by, or encountering, somebody will-
`ing to take notice that he or she is a lost person.
`Location services are considered most urgent for
`those who live at home, especially since the costs of
`institutionalization are high. However, even those who
`
`IEEE Communications Magazine • April 1998
`
`69
`
`Apple, Inc. Exhibit 1007 Page 4
`
`

`
`live in community care facilities can benefit from such a device.
`The need arises because the facility may not be walled in and
`because residential facilities often permit residents freedom of
`movement within the facility. Such facilities seldom have suffi-
`cient staff to constantly monitor the whereabouts of each individ-
`ual patient. Alzheimer’s patients are generally not distinguishable
`by appearance from those whose memory is intact, and therefore
`their comings and goings do not evoke as much attention as those
`of patients who are visibly ill. A nursing home that loses a patient
`entrusted to its care is exposed to a very high liability risk.
`A personal location system such as that required for
`Alzheimer’s patients is shown in Fig. 4. By following the sequence
`of events, by either automatic detection or caregiver report, the
`patient is determined to be missing and the location system is
`invoked (1). The operations center (2) uses a conventional paging
`service (3) to activate the personal location unit (PLU), which
`activates and transmits a location signal (4). The surrounding
`receiver stations, coordinated via a terrestrial network, capture
`the PLU signal (5), perform preliminary processing, and send the
`reduced data to the center of operations (6). The center of oper-
`ations calculates the position (7) and sends the result to the
`requesting person or emergency response agency (8), or to a
`computer for automated tracking applications such as parolee
`tracking, which is discussed below.
`In ongoing work, we are defining the process by which emer-
`gency crews will use the location information to locate and recov-
`er the patient.
`
`TRACKING CRIMINALS
`Another application STC is studying is the use of SLS for tracking
`and monitoring people in criminal justice applications.
`In this case, the requirement is for a technique that can pro-
`vide a wide-area low-cost radio location system for electronic
`monitoring and location of offenders who have been released into
`the community on parole, probation, or pretrial release. The
`
`need to solve this problem is well recognized [7], and this need
`becomes continuously more urgent as increasing numbers of indi-
`viduals are being released from overcrowded detention centers,
`or are placed under observation for a long time under court
`orders while awaiting trial.
`Electronic monitoring (EM) is already being used for many
`correctional purposes, but existing systems are quite rudimentary.
`Current applications of EM devices include supervision of curfew
`confinements, home detention, and home incarceration monitor-
`ing. Such devices are sometimes called “first-generation” moni-
`toring devices [7] and involve merely the detection of proximity
`of the offender to a fixed location or detection of perimeter
`crossings. In such perimeter detection systems, an alert (or alarm
`signal) is triggered when the individual crosses a threshold. The
`radio technology used is similar to what is commonly used in
`retail theft control systems and libraries for the checkout of
`books, but the prisoner monitoring system uses a secure bracelet
`which cannot readily be removed by the subject without triggering
`an alert.
`The more important problem concerns electronic monitoring
`over a larger range, providing more freedom to the wearer of the
`device but also providing a record of the movements of the
`offender within the community. Such devices are known as “sec-
`ond-generation” monitoring devices. An alarm would be triggered
`when the person being monitored is not within a specified geo-
`graphical area or approaches its preprogrammed limits. There is
`significant interest in such technology for probation and parole.
`In many cases, it can also be considered as an alternative to
`imprisonment [8, 9].
`When electronic monitoring can be expanded to routinely
`include supervision of individuals restricted to stay within a larger
`specified area, it will become possible for some persons who now
`have to be confined in prison to instead stay outside the prison
`while being monitored electronically. Unfortunately, the existing
`technologies for position location have many drawbacks: they
`either are ineffective within buildings, have limited range of cov-
`
`Base stations
`located at existing
`cellular base stations
`measure signal
`parameters
`
`5
`
`4
`PLU emits
`known signal
`
`3
`
`Paging signal
`activates PLU
`
`Paging
`transmitter
`
`PTN
`
`PLU
`
`6
`Base stations send
`parameters to center of operations
`
`Low data rate lines
`(ISDN or frame relay)
`
`7
`Computer
`calculates position
`
`2
`Center of
`operations
`pages PLU
`
`Map
`1
`database
`Application host
`requests the position of
`a particular unit ID or
`group of units
`
`Subscriber
`database
`
`8
`Center of operations
`reports unit location
`to requesting host
`
`n Figure 4. Person location/tracking using the SLS.
`
`70
`
`IEEE Communications Magazine • April 1998
`
`Apple, Inc. Exhibit 1007 Page 5
`
`

`
`erage or have poor accuracy, the unit carried by the individual
`being tracked is large; or the unit consumes so much power that
`it drains batteries too rapidly. The SLS may offer a possible solu-
`tion to these problems.
`It is likely that a position location system, such as SLS, will be
`combined with first-generation perimeter alarm systems, and
`designed to be activated, or deactivated, only when the individual
`crosses a specified boundary.
`ACKNOWLEDGMENTS
`This publication was made possible in part by grant number
`R41AG12573-01 from the National Institutes of Health (NIH);
`award number 97-LB-VX-K003 from the Office of Justice Pro-
`grams, National Institute of Justice (NIJ), Department of Justice;
`and grant number DMI-9560808 from the National Science
`Foundation (NSF). Its contents are solely the responsibility of the
`authors and do not necessarily represent the official views of the
`NIH, the U.S. Department of Justice, or the NSF.
`In addition we would like to thank Jay Weitzen and Haifeng
`Qiu for their valuable contributions to this publication.
`
`REFERENCES
`[1] Notice of Proposed Rulemaking, Docket 94-102, FCC, 1994.
`[2] “Wireless Location Services: 1997,” Strategis Group, 1997.
`[3] T. S. Rappaport, J. H. Reed, and B. D. Woerner, “Position Location Using
`Wireless Communications on Highways of the Future,” IEEE Commun. Mag.,
`Oct. 1996, pp. 33–41.
`[4] K. D. Melillo and M. Futrell, “Wandering: Survey of Formal Care Providers
`and Informal Caregivers Regarding the Use of a Low-Cost Patient Locator
`Unit,” submitted to J. Gerontological Nursing, 1997.
`[5] L. Morishita, “Wandering Behavior,” Alzheimer’s Disease: Treatment and
`Long-Term Management, Cummings and Miller, Eds. 1990, New York: Mar-
`cel Dekker, pp. 157–76.
`
`[6] D. A. Evans et al., “Prevalence of Alzheimer’s Disease in a Community Popu-
`lation of Older Persons,” J. AMA, vol. 18, 1989, pp. 2551–56.
`[7] J. Hoshen, J. Sennott and M. Winkler, “Keeping Tabs on Criminals,” IEEE
`Spectrum, 1995, pp. 26–32.
`[8] J. K. Stewart, E. W. Zedlewski, and L. E. Ray, “The Economics of Disincarcer-
`ation,” Selective Notification of Information, U.S. Dept. of Justice, Nat’l.
`Inst. of Justice/NCJRS, NIJ Reports/SNI 185, vol. May, pp. 19–84.
`[9] P. J. P. Tak, “Alternatives to Imprisonment: International Summaries, Nat’l.
`Inst. of Justice/NCJRS, NCJ 114272.
`
`BIOGRAPHIES
`JAMES M. ZAGAMI (sig@world.std.com) is senior signal processing engineer at
`Signatron Technology Corporation. He received his B.S. in electrical engineering
`from the University of Massachusetts at Lowell in 1990. He currently has a
`patent pending involving radio location.
`
`STEEN A. PARL (sig@world.std.com) is president of Signatron Technology Corpo-
`ration. He received his Ph.D. in electrical engineering from the Massachusetts
`Institute of Technology in 1974, and his M.S. degree in electrical engineering
`from the Technical University of Denmark in January, 1970. He has published
`approximately 40 papers and holds five patents, with another patent pending.
`
`JULIAN J. BUSSGANG (jjbussgang@aol.com) founded Signatron, Inc. (predecessor
`of Signatron Technology Corporation) in 1962 and is a highly regarded commu-
`nications expert. He received his Ph.D. in applied physics from Harvard Universi-
`ty in 1955, and his M.S. in electrical engineering from the Massachusetts
`Institute of Technology in 1951. He holds several patents and has published
`numerous papers.
`
`KAREN DEVEREAUX MELILLO (karen_melillo@uml.edu) is a professor in the Depart-
`ment of Nursing at the University of Massachusetts Lowell. She received her
`Ph.D. from Brandeis University in 1990, and her M.S. in gerontological nursing
`from the University of Massachusetts at Lowell in 1978. She is published in
`many professional journals, and has served as principal investigator for several
`grants and contracts.
`
`IEEE Communications Magazine • April 1998
`
`71
`
`Apple, Inc. Exhibit 1007 Page 6