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Three-Dimensional Magnetic Tracking of

Three-Dimensional Magnetic Tracking of
Three-Dimensional Magnetic Tracking of

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IEEE TRANSACTIONS ON MAGNETICS, VOL. 40, NO. 3, MAY 2004
Three-Dimensional Magnetic Tracking of Biaxial Sensors
Eugene Paperno and Pavel Keisar
Abstract—We present an analytical (noniterative) method for tracking biaxial magnetic sensors. Low-resolution regions (LRRs) of a biaxial transmitter are determined for the tracking of a triaxial sensor. These regions represent the reciprocal LRRs of a biaxial sensor that is tracked with a triaxial transmitter. The LRRs’ configuration suggests that at least four triaxial transmitters should be used to track a biaxial sensor. At least one of the transmitters will always avoid the sensor’s reciprocal LRRs. We show, on the other hand, that there are no LRRs for estimations of distance between the transmitter and the sensor. This makes it possible to triangulate a biaxial sensor with a triad of transmitters, instead of four. Thanks to a better distance resolution, compared to the resolution of coordinates, the triangulation provides practically the same location resolution and update rate as those reached by conventional methods of tracking triaxial sensors. This is true despite the need to operate a greater number of transmitting coils. Index Terms—Biaxial sensor, distance resolution, location resolution, low-resolution region, magnetic tracking, reciprocal problem.
I. INTRODUCTION ECENT applications of high-speed magnetic tracking such as intrabody navigation of medical instruments [1] and eye tracking [2] can benefit from employing subminiature magnetic sensors. A magnetic tracking sensor can radically be simplified and miniaturized if the number of its axes is reduced from three to two (see Fig. 1). Such simplification can also pave the way for introducing flat, completely integrated, solid-state sensors to magnetic tracking. Triaxial sensors currently employed in high-speed, noniterative magnetic tracking are rather bulk ( 100 mm ) and complex [1]. Such sensors typically consist of three concentric orthogonal induction coils. It is difficult to combine three concentric coils in a single miniature device. It is even more difficult to achieve a good orthogonality of the subminiature coil assembly. Biaxial solid-state sensors are technologically much simpler, more miniature, and geometrically precise. For instance, nonencapsulated solid-state sensors based on anisotropic magnetoresistance (AMR) or giant magnetoresistance (GMR) occupy less than a 2 mm volume. Microlithography provides precise orthogonality to the solid-state sensors. Compared to uniaxial sensors, biaxial sensors can be tracked with the help of fast noniterative algorithms. Biaxial sensors also
Manuscript received August 15, 2002; revised August 15, 2002. This work was supported in part by Analog Devices, Inc. and the Ivanier Center for Robotics Research and Production Management. E. Paperno is with the Department of Electrical and Computer Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel (e-mail: paperno@ee.bgu.ac.il). P. Keisar is with the Lattice Semiconductor Corporation, Tel-Aviv 69719, Israel (e-mail: pavel.keisar@https://www.sodocs.net/doc/d718569707.html,). Digital Object Identifier 10.1109/TMAG.2004.826615
R
Fig. 1. Magnetic tracking. (a) The triaxial sensor is tracked with the biaxial transmitter. (b) The biaxial sensor is tracked with the triaxial transmitter.
enable a six-degrees-of-freedom (DOF) tracking, whereas only a five-DOF tracking is possible with uniaxial sensors. Unfortunately, no reliable analytical (noniterative) methods for magnetic tracking of biaxial sensors seem to be described in literature. The present work is aimed at bridging this gap. II. NONITERATIVE MAGNETIC TRACKING IN THREE-DIMENSIONAL (3-D) SPACE Magnetic tracking in 3-D space can be based on simple and fast analytical procedures [3], [4] if the vector outputs of the receiver (magnetic sensor) can be combined into an orientation invariant scalar signal that is proportional to the total field magnitude at the sensor’s location. In this case, the sensor location can be calculated first by processing the scalar signals received
0018-9464/04$20.00 ? 2004 IEEE

PAPERNO AND KEISAR: 3-D MAGNETIC TRACKING OF BIAXIAL SENSORS
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cannot be reoriented like it can be done by electrically rotating the triaxial transmitter in [3]. It is possible to keep the triaxial sensor in Fig. 2(a) away from the LRRs by simply limiting its location freedom. However, entering an LRR is unavoidable while solving the reciprocal problem of tracking a biaxial sensor in Fig. 2(b). It is generally impossible to limit orientation freedom of the sensor and to avoid the situations where the transmitter is within one of the sensor’s reciprocal LRRs. It seems that the only way of maintaining the resolution at the acceptable level is to increase the number of transmitters and to locate them in such a pattern that at least one of the transmitters is always away from the sensor’s reciprocal LRRs. To decide on the number of transmitters needed and their spatial pattern, we should carefully investigate the reciprocal LRRs of a biaxial sensor. III. LOW-RESOLUTION REGIONS OF A BIAXIAL SENSOR Let us consider two different methods of magnetic tracking with biaxial transmitters, [3] and [4]. We shall find the LRRs of the transmitter. These regions will represent the reciprocal LRRs of a biaxial sensor. For the sake of simplicity and without loss of generality, we assume that the magnetic moment of the A m and the sensor is located on a transmitting coils unit (1-m radius) spherical segment, as shown in Fig. 3(a). According to method [3], the - and -axis transmitting coils [coil #1 and coil #2 in Fig. 3(a)] are excited in sequence by ac current of frequency . The sensor’s location is found by processing the corresponding quasi-static magnetic dipole field and their dot product seen by the amplitudes sensor (indexes 1 and 2 are related here to transmitting coils #1 and #2, correspondingly)
Fig. 2. Magnetic tracking reliability. (a) It is possible to limit location freedom of the sensor, and it can avoid the low-resolution region near the biaxial transmitter axis. (b) It is generally impossible to limit orientation freedom of the sensor, and the transmitter cannot avoid the reciprocal lowresolution region near the sensor’s axis. (Not all low-resolution regions are shown in this figure.)
(1)
from different transmitters; then, the sensor’s orientation can be found with reference to the known total field vectors at the sensor’s location. It is apparent that the simplest sensor suitable for the above procedure should be a triaxial one to supply both the vector and scalar outputs. The simplest transmitter can be a biaxial one. Such a transmitter provides enough information for localizing a triaxial sensor in a given quadrant of space [3], [4]. Reciprocity requires that the magnetic coupling remains the same if the sensor and the transmitter replace each other. Hence, it seems possible, at first sight, to localize a biaxial sensor with a triaxial transmitter [see Fig. 1(b)] by measuring the coupling between the transmitting and the sensing coils and then solving the reciprocal problem [3]. However, the difficulty is that there are low-resolution regions (LRRs) around the transmitter. It is known, for example, that the location resolution of the tracking drastically decreases near the coordinate axes of a triaxial transmitter [3]. The similar LRRs should be expected for a biaxial transmitter as well [see Fig. 2(a)]. To make things worse, the LRR shown in Fig. 2(a)
where the scalar signals and from the sensor vector outputs, such that
are combined
(2)
Solution of (1) gives the sensor’s coordinates
(3)

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IEEE TRANSACTIONS ON MAGNETICS, VOL. 40, NO. 3, MAY 2004
TABLE I SIGNAL-TO-NOISE RATIO CALCULATION
(7)
Fig. 3. Magnetic sensor location and structure. (a) Magnetic sensor is located at a fixed distance r = 1 m from the transmitter. Note that z = 1 x y . (b) Independent noise signals  ;  ;  are superimposed on the corresponding sensor vector outputs S ; S ; S .
p 0 0
can be found by analyzing the following equation for the total scalar field seen by the sensor:
According to method [4], the transmitting coils are excited in quadrature at a quasi-static frequency , and the sensor’s location is found as follows:
(8) The field components and in (4), (6), and (7) can be extracted from the sensor total output with the help of synchronous detection. To determine the LRRs of the biaxial transmitter in Fig. 3(a), and are we suppose that independent noise signals superimposed on the corresponding sensor vector outputs [see Fig. 3(b)]. We also suppose that root-mean-square (rms) values and of the above noise signals are equal relative to the maximum magnitude of the sensor weak vector outputs (see a practical case in Table I). of methods [3] and [4] We can now find the resolution as a function of the sensor’s location on the spherical surface in Fig. 3(a)
(4)
where is the distance between the transmitter and the sensor, is the azimuth, and is the elevation angle [see Fig. 3(a)], such that (5) The azimuth and the total field extremes in (4)
(9) , and are the rms estimation errors of the correwhere sponding sensor’s coordinates.
(6)

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The , and errors can be determined with the help of Gauss’s error propagation rule. Equation (3) suggests the following system of partial derivatives for method [3]:
(10)
Equation (5) suggests the following system of partial derivatives for method [4]:
(11)
where
(12)
Fig. 4. Location resolution  calculated for the sensor in Fig. 3(a) as a function of the sensor’s coordinates x and y in (a) and as a function of  and (contour plots) for method [3] in (b) and method [4] in (c). The bold numbers , measured in in parts (b) and (c) represent the location resolution,  millimeters.
and
To evaluate the rms noise magnitudes , and of the sensor scalar outputs , and , we neglect the second-order noise terms in the following equations for the corresponding noise signals: We now can write according to (13) (13)
(14)
(15)

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IEEE TRANSACTIONS ON MAGNETICS, VOL. 40, NO. 3, MAY 2004
Fig. 5. Simulation of the sensor’s location estimates for r = 1 m,  = 45 and different under noise conditions  = 10 (a) according to (3) and (b) according to (4). Each cube corresponds to a 1 1 1 mm area around the true sensor’s location. The black dots within the cubes are the location estimations (500 total for each cube). The gray dots on the cubes’ facets are projections of the dots within the cube.
2 2
Fig. 6. Magnetic tracking errors. (a) The triaxial sensor can avoid the low-resolution regions related to the biaxial transmitter. (b) While solving the reciprocal problem, a triad of the triaxial transmitters cannot always avoid the reciprocal low-resolution regions related to the biaxial sensor.
and in the same way (16) According to (14) Fig. 4(b) and (c) shows that the elevation angle should be for method [3] and for method [4] to provide a resolution mm rms in a 200-Hz bandwidth (see Table I). The elevation angles that are beyond the above limits represent the LRRs of the biaxial transmitter [see Fig. 6(a)]. Similar LRRs should be related to the biaxial sensor while solving the reciprocal problem [see Fig. 6(b)]. Fig. 6(b) makes it clear that the triad of transmitters cannot always avoid the reciprocal LRRs of the sensor. At least one more transmitter should be added to the transmitting array for a reliable tracking. IV. TRACKING WITH A TRIAD OF TRANSMITTERS Rather than to raise the number of transmitters in Fig. 6(b) beyond three, it is worth examining the resolution of the distance estimation by each of the transmitters. Three different and reliable distance estimates obtained with a triad of transmitters [see
(17)
Substitution of , and from (13)–(15) into (10), (11) and taking the derivatives yield the location resolution of methods [3] and [4]. as a function of the Fig. 4(a) shows the resolution sensor’s coordinates and . Fig. 4(b) and (c) show contour as a function of the azimuth and elevation plots of the angles. Fig. 5 shows the simulation of the sensor’s location and different values of . estimates for a As seen from Figs. 4 and 5, the location resolution of both methods [3] and [4] rapidly degrades when coordinate approaches either zero or unity.

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estimation error can be evaluated assuming that The the sensor coordinates are measured with independent errors and neglecting the second-order terms
(19) The rms value of the estimation error can be found then as (20) which, considering (10) and (15)–(17), leads to
(21) Since (22) then the rms value of the distance estimation error, or the distance resolution, can be written as (23) For method [4], the distance resolution can be found from (12) and (22) as follows: (24) Comparison between (23) and (24) suggests that the distance resolution of method [4] is at least four times better than that of method [3]. Examination of (24) shows that for method [4] mm for any location of the sensor on the unit radius sphere in Fig. 3(a). In other words, there are no LRRs for the distance estimation. As a result, it is always possible to localize (triangulate) a biaxial sensor with a triad of triaxial transmitters. It is quite obvious that the triangulation resolution depends on the distance between the transmitters in the triad and the distance between the triad and the sensor [see Fig. 7(a)]. A simulation of the sensor location estimates is shown in Fig. 7(b) for the triad where the transmitters are uniformly situated on a circle of a 0.3 m radius. A comparison of Fig. 7(b) against Fig. 5 shows a two- to threefold improvement in the location resolution. It means that the increase in the total number of transmitters from one biaxial transmitter in Fig. 1(a) to three triaxial transmitters in Fig. 7(a) will not finally demand decreasing the update rate of the location estimation. To keep the same update rate of the location estimation, each of the nine transmitting coils in Fig. 7(a) should be operated during the time intervals that are by a factor of 4.5 shorter than the time intervals of operating the two transmitting coils in Fig. 1(a). This increases by the same factor both the signal and noise bandwidth. As a result, the location reso, lution shown in Fig. 7(b) will be reduced by a factor of assum-ing that the magnitude of transmitted signals is kept constant (despite reducing their duty cycle) and the noise interfering the system is white. The above reduction will equal the location
Fig. 7. Magnetic tracking with a triad of transmitters. (a) Magnetic sensor is located at a fixed distance r = 1 m from the triad of transmitters. (b) Simulation of the sensor’s location estimates under noise conditions  = 10 . Each cube corresponds to a 1 1 1 mm area around the true sensor’s location. The dots within the cubes are the location estimations (500 dots total for each cube).
2 2
Fig. 7(a)] will be enough to localize the sensor with triangulation technique. For method [3], the distance between the transmitter and the sensor [see Fig. 3(a)] is related to the sensor’s coordinates as follows: (18)

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