The department’s research activities encompass several broad areas, reflecting the multi-disciplinary nature of the control and mechatronics field. These include:
• Smart sensors and actuators
• Process tomography
• Intelligent machines
• Advanced and intelligent control algorithms
• Process control and its advancements
• Real-time control system
• Robot design and intelligent robot controllers
• Modeling and control of mechatronic systems
• Industrial automations
• Nanotechnology-based mechatronics and robotics
مدیر وبلاگ :
1.4 GNSS/INS INTEGRATION OVERVIEW
1.4.1 The Role of Kalman Filtering
It has been called “navigation’s integration workhorse”  for the essential
role it has played in navigation and especially for integrating different navigation modes. Ever since its introduction in 1960 , the Kalman filter has
played a major role in the design and implementation of most new navigation
systems as a statistically optimal method for estimating position using noisy
measurements. Because the filter also produces an estimate of its own accuracy, it has also become an essential part of a methodology for the optimal
design of navigation systems. The Kalman filter has been essential for the
design and implementation of every GnSS. It is unlikely that the first GnSS
(GPS) could have been built without it.
using the Kalman filter, navigation systems designers have been able to
exploit a powerful synergism between GnSSs and InSs, which is possible
because they have very complementary error characteristics:
• Short-term position errors from the InS are relatively small, but they
degrade significantly over time.
• GnSS position accuracies, on the other hand, are not as good over the
short term, but they do not degrade with time.
The Kalman filter takes advantage of these characteristics to provide a
common, integrated navigation implementation with performance superior to
that of either subsystem (GnSS or InS). By using statistical information about
the errors in both systems, it is able to combine a system with tens of meters
position uncertainty (GnSS) with another system whose position uncertainty
degrades at kilometers per hour (InS) and achieve bounded position uncertainties in the order of centimeters (with differential GnSS) to meters.
GnSS/InS InTEGrATIOn OvErvIEW 31
The Kalman filter solves for the solution with the least mean-squared error
by using data weighting proportional to statistical information content (the
inverse of uncertainty) in the measured data. It combines GnSS and InS
1. track drifting parameters of the sensors in the InS, so that InS performance does not degrade with time when GnSS is available
2. improve overall performance even when there are insufficient satellite
signals for obtaining a complete GnSS solution
3. allow the InS to navigate with improved initial error whenever GnSS
signals become unavailable
4. improve GnSS signal reacquisition when GnSS signals become available again by providing better navigation solutions (based on InS data)
5. use acceleration and attitude rate information from the InS for reducing
the signal phase-tracking filter lags in the GnSS receiver, which can
significantly improve GnSS reliability during periods of high maneuvering, jamming, or reduced signal availability.
The more intimate levels of GnSS/InS integration necessarily penetrate
deeply into each of the subsystems in that it makes use of partial results that
are not ordinarily accessible to users. To take full advantage of the offered
integration potential, we must delve into technical details of the designs of
both types of systems.
188.8.131.52 Military Applications The rationale for developing the navistar
GPS system was based, in part, on economic considerations—in terms of how
many inertial systems it could replace. However, the ability to integrate GPS
with InS also enabled military applications that were not possible before. It
would lead to a new generation of high-precision military weaponry, improving military effectiveness while reducing collateral damage. Most missiles were
already using inertial sensors for guidance and control, so the transition to
integrated GnSS/InS navigation was natural.
Most military applications of inertial navigation were already using other
navigation aids for limiting the growth of inertial navigation errors with time.
The u.S. navy had begun using satellites for aiding shipboard inertial navigation decades before GnSS became available, and most military InSs were
being adapted to use GPS before it was operational. It has resulted in superior
navigation performance at low marginal cost.
184.108.40.206 Civilian and Commercial Applications The availability of GnSS
also allowed for integrated GnSS/InS navigation systems accurate enough
for automated grading, plowing, and surface mining. The resulting relaxation
of inertial sensor stability requirements and advances in fabrication technologies have also combined to lower costs to the point where low-performance
GnSS/InS systems can be embedded in high-end consumer products. This
market is likely to grow even more as costs fall due to increasing production
Details of Section 1.4 are given in Chapters 10 through 12
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سه شنبه 17 مرداد 1396 06:41 ق.ظ
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