Data processing: measuring – calibrating – or testing – Measurement system – Orientation or position
Reexamination Certificate
2000-02-14
2002-11-26
Shah, Kamini (Department: 2863)
Data processing: measuring, calibrating, or testing
Measurement system
Orientation or position
C702S153000, C324S207170, C367S127000
Reexamination Certificate
active
06487516
ABSTRACT:
This application contains Microfiche of one page, 21 frames.
FIELD OF THE INVENTION
The present invention relates generally, to positioning systems and more particularly to positioning systems employing alternating electromagnetic fields, as well as to apparatus for localization and tracking.
BACKGROUND OF THE INVENTION
Various types of positioning systems which employ alternating electromagnetic fields are known. The following U.S. Patents and foreign patent documents are believed to represent the state of the art for positioning systems:
U.S. Pat. Nos. 4,054,881 and 4,314,251 to Raab; U.S. Pat. No. 4,622,644 to Hansen; U.S. Pat. No. 4,737,794 to Jones; U.S. Pat. Nos. 4,613,866, 4,945,305 and 4,849,692 to Blood, U.S. Pat. Nos. 4,017,858 and 4,298,874 and 4,742,356 to Kuipers; U.S. Pat. No. 5,168,222 to Volsin et al; U.S. Pat. No. 5,0170,172 to Weinstein; and U.S. Pat. No. 5,453,686 to Anderson; WO 94/04938 to Bladen; U.S. Pat. No. 5,953,683 to Hansen; U.S. Pat. No. 5,831,260 to Hansen; U.S. Pat. No. 5,767,960 to Orman; U.S. Pat. No. 5,767,669 to Hansen; U.S. Pat. No. 5,744,953 to Hansen; U.S. Pat. No. 5,742,394 to Hansen; U.S. Pat. No. 5,640,170 to Anderson; U.S. Pat. No. 5,600,330 to Blood; U.S. Pat. No. 5,307,072 to Jones; U.S. Pat. No. 4,945,305 to Blood; U.S. Pat. No. 4,710,708 to Rorden; U.S. Pat. No. 4,346,384 to Raab; U.S. Pat. No. 4,328,548 to Crow; U.S. Pat. No. 4,298,874 to Kuipers; U.S. Pat. No. 3,983,474 to Kuipers; U.S. Pat. No. 3,868,565 to Kuipers; 3,644,825 to Davis
U.S. Pat. No. 4,710,708 to Rorden describes a positioning system which employs only one magnetic coil.
Genetic algorithms are described in
Genetic algorithms in search: optimization and machine learning,
D. Goldberg, 1989; and
An introduction to genetic algorithms,
Melanie Mitchell, 1996.
PLL technology is described in
Phase locked loop: simulation and applications,
by Roland E. Best, McGraw-Hill Book Company, ISBN 0070060517.
The theory of non-linear filtering and its applications are discussed in:
H. J. Kushner, “Approximations to Optimal Nonlinear Filters”. IEEE Trans. A C., Vol. AC-12, No. 5, October 1967;
A. Gelb, J. F. Kaspar,. Jr., R. A. Nash, Jr., C. E. Price, and A. A. Southerland, Jr.,“Applied Optimal Estimation”, M.I.T. Press, Cambridge, Mass., 1974;
B. D. O. Anderson, and J. B. Moore, “Optimal Filtering”, Prentice-Hall, Englewood Cliffs, N.J., 1979;
A. H. Jazwinski, “Stochastic Processes and Filtering Theory”, Academic Press, New York 1971, and
M. S. Grewal, and A. P. Andrews, “Kalman Filtering”, Prentice-Hall, Upper Saddle River, N.J., 1993,
The field equation law is discussed in:
J. D. Jackson, “Classical Electrodynamics”, John Wiley & Sons, New York New York, 1975.
The application of Extended Kalman Filters (EKF) to tracking in the context of radar is discussed, for example, in U.S. Pat. Nos. 5,075,694, 4,179,696, 3,952,304 and 3,935,572. Other tracking systems are discussed, for example, in U.S. Pat. Nos. 5,095, 467 and 4,855,932.
The Kalman Filter is a standard tool for “data fusion” of different sensors. In U.S. Pat. No. 5,416,712 GPS signals and dead reckoning are combined by a Kalman Filter, and where the gyro bias is also calibrated. In U.S. Pat. No. 5,645,077 automatic drift compensation is discussed,
Simulated annealing-based algorithms are described in:
B. Aarts and J. Korst, “Simulated Annealing and Boltzman Machines: A Stochastic Ap
1
proach to Combinatorial Optimization and Neural Computing”, John Wiley and Sons Ltd. (ISBN: 0471921467);
M. E. Johnson (Ed.) “Simulated Annealing (Sa and Optimization: Modem Algorithms with VLSI, Optimal Design and Missile Defense Applications)”, Amer. Sciences Pr. (ISBN: 0935950184); and
R. Azencott (Ed.), “Simulated Annealing: Parallelization Techniques”, Wiley Interscience Series in Discrete Mathematics, John Wiley and Sons Ltd. (ISBN: 0471532312),
The disclosures of all publications mentioned in the specification and of the publications cited therein are hereby incorporated by reference,
SUMMARY OF THE INVENTION
The present invention provides improved apparatus and method for positioning and tracking objects, and also to a non-linear Kalman Filter tracker.
A genetic algorithm is typically employed for solving the position equation to obtain the position and orientation of the detector.
A particular advantage of a preferred embodiment of the present invention is conservation of bandwidth by cessation of operation of transmitters, which are not providing useful information.
Selective activation of the transmitters is preferably performed periodically. The period is preferably selected automatically by the system to match the expected pace of change in the location of the moving body and the estimated distance between transmitters.
There is thus provided in accordance with a preferred embodiment of the present invention a tracking and positioning system including a plurality of transmitters distributed within a working space, and at least one sensors attached to at least one moving object and operative to sense transmissions arriving from the plurality of transmitters, a dynamic transmission activator operative to track at least one position parameters of at least one of the sensors and to selectively activate and deactivate individual sets of at least one transmitters from among the plurality of transmitters, at least partly responsively to at least one position parameters of at least one of the sensors.
Further in accordance with a preferred embodiment of the present invention the dynamic transmission activator is operative to activate at least one individual transmitter from among the plurality of transmitters if and only if at least one sensor is within the operating range of the individual transmitter.
Still further in accordance with a preferred embodiment of the present invention the dynamic transmission activator is operative to deactivate at least one individual transmitter from among the plurality of transmitters if and only if all sensors are outside of the operating range of the individual transmitter.
There is also provided in accordance with yet another preferred embodiment of the present invention a tracking method for tracking a moving object whose initial position is substantially unknown, the method including the steps of using a genetic algorithm to initially position the moving object, and tracking the moving object using a Kalman filter tracking method.
Further in accordance with a preferred embodiment of the present invention, the tracking method also includes at least once repositioning the moving object, during tracking, using the genetic algorithm.
A block diagram of the disclosed system, for positioning and tracking objects, is shown in
FIG. 1
d.
In accordance with a preferred embodiment of the present invention a system comprises of N transmitters, where N≧6, and at least one probe sensor which detects at least 6 electromagnetic signals, each characterized by its own frequency. The probe sensor typically comprises a single magnetic field detector that is connected to a digital signal processing circuit. The analog output of the magnetic signal detector is a voltage signal proportional to the superposition of the N magnetic field transmitters at the coordinates x
i
, y
i
, z
i
, &thgr;
i
, &phgr;
i
, where the index i denotes the position of the magnetic coil i. It is a particular feature of a preferred embodiment of the present invention that the antenna coils need not be exactly mutually orthogonal and certainly need not be arranged such that the centers of the antenna coils coincide.
The analog signal is digitized and is introduced to an integrated digital signal processor block, as an input data. The digitized input data from one of the magnetic detectors is then used by the digital signal processor unit to compute the position and orientation coordinates of the magnetic detector. The output from the digital signal processor unit is then transferred to the Data Communication unit and then to the System Control Unit. The refresh rate of the output data is typically of the order of few times per second
Netmor Ltd.
Shah Kamini
Townsend and Townsend / and Crew LLP
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