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Given the linearized error model of Section 1053, by observability analysis it is straightforward to show that even over intervals containing both magnetometer and accelerometer measurements, the full error state is not

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Finding the current date and time is useful, but in many cases, you also need to know where your Mac s clock is set in relation to Greenwich Mean Time (GMT) To do so, use the time to GMT command, which returns the time in seconds between your Mac s time zone and GMT For example, if you re stuck outside of Memphis with a mobile Mac, time to GMT typically returns 18000, which is five hours behind GMT, whereas if you re in New Zealand, time to GMT typically returns 43200, or twelve hours ahead of GMT To get the number of hours, divide the result of time to GMT by the hours constant:

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observable unless the system is rotating The few interesting questions relate to levels of observability, performance analysis, and tradeo studies are: For a stationary system, what is the expected level of performance For a system moving with lateral velocity, how does the lack of knowledge concerning in a ect the system performance How does this limit the applicability of this AHRS approach How much performance would be lost by eliminating the accelerometer biases from the model How much performance could be gained by estimating scale factor errors These questions are left as exercises for the reader

You can use the standard operators discussed in 4 to compare dates and times For example, each of the following comparisons works for finding out whether the current date lies before Independence Day 2012:

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This section contains application results from laboratory bench testing During the experiment, magnetometer measurements were not available Therefore, in this experiment, only pitch and roll estimates are of interest The IMU sampling rate is approximately 172 Hz The IMU is manipulated by hand through a sequence of maneuvers For the rst and last few seconds, the IMU is stationary in the same position with the same orientation The raw IMU data is shown in Figures 102 and 103 The non-smooth nature of the data should not be interpreted as noise The standard deviation of the gyro and accelerometer measurements are 40 10 3 rad m and 22 10 2 2 s s

(current date) comes before date "Wednesday, July 04, 2012 12:00:00 AM" (current date) < date "Wednesday, July 04, 2012 12:00:00 AM" (current date) is less than date "Wednesday, July 04, 2012 12:00:00 AM"

This level of noise is too small to be resolved at the scale used in these gures Instead, the lack of smoothness is caused by the gyro handling The gyros are speci ed for input rates of 90 deg ; therefore, the roll gyro s measuring p saturates for t [14827, 14837] This saturation causes error in the compute attitude, which the system is able to estimate and remove The curves in the top graph in Figure 104 show the roll and pitch angles as computed by the AHRS approach presented in this chapter It is natural to consider whether eqns (1014 1015) could be used throughout instead of the presented approach For comparison, the curves in the bottom graph of Figure 104 show the roll and pitch angles computed using eqns (1014 1015) Figure 105 magni es a portion of the time axis to allow a more detailed comparison Notice the following:

60 3600 86,400 604,800

100 Ang rate, p, dps 50 0 50 100 100 Ang rate, q, dps 50 0 50 100 100 Ang rate, r, dps 50 0 50 100 0 50 100 Time, t, s 150 200 0 50 100 150 200 0 50 100 150 200

With the patient upright, the angle of the mandible, medial edge of each sternocleidomastoid muscle, submental crease, and the thyroid notch are marked Preoperative marking is imperative because when the patient lies supine, the fatty accumulations tend to shift and occasionally disappear Submental liposuction can be performed under local, intravenous sedation, or general anesthesia as subject to the surgeons preference and patients needs After administration of adequate sedation and preparation and draping of the patient, the marked region is in ltrated with local anesthetic