Looking for suggestions or pointers on how to track the gravity vector in 6D data. -- Randy Yates Digital Signal Labs http://www.digitalsignallabs.com
Gravity Vector Tracking
Started by ●May 1, 2013
Reply by ●May 1, 20132013-05-01
On 5/1/2013 2:54 PM, Randy Yates wrote:> Looking for suggestions or pointers on how to track the gravity vector > in 6D data. >http://en.wikipedia.org/wiki/Equivalence_principle VLV
Reply by ●May 1, 20132013-05-01
Vladimir Vassilevsky <nospam@nowhere.com> writes:> On 5/1/2013 2:54 PM, Randy Yates wrote: >> Looking for suggestions or pointers on how to track the gravity vector >> in 6D data. >> > > http://en.wikipedia.org/wiki/Equivalence_principleHi Vlad, Thanks for that. Are you saying it's impossible? How does a navigational system account for gravity, e.g.? -- Randy Yates Digital Signal Labs http://www.digitalsignallabs.com
Reply by ●May 1, 20132013-05-01
Randy Yates <yates@digitalsignallabs.com> writes:> Vladimir Vassilevsky <nospam@nowhere.com> writes: > >> On 5/1/2013 2:54 PM, Randy Yates wrote: >>> Looking for suggestions or pointers on how to track the gravity vector >>> in 6D data. >>> >> >> http://en.wikipedia.org/wiki/Equivalence_principle > > Hi Vlad, > > Thanks for that. Are you saying it's impossible? How does a navigational > system account for gravity, e.g.?PS: The only way I know of is to calibrate it when the object is known to be at rest. In a perfect world, that will work, but real-world sensors (even when calibrated) have offsets and other nonlinearities that will erode the accuracy of gravity vector determination over time. -- Randy Yates Digital Signal Labs http://www.digitalsignallabs.com
Reply by ●May 1, 20132013-05-01
On 5/1/2013 3:22 PM, Randy Yates wrote:> Vladimir Vassilevsky <nospam@nowhere.com> writes: > >> On 5/1/2013 2:54 PM, Randy Yates wrote: >>> Looking for suggestions or pointers on how to track the gravity vector >>> in 6D data. >>> >> >> http://en.wikipedia.org/wiki/Equivalence_principle > > Hi Vlad, > > Thanks for that. Are you saying it's impossible? How does a navigational > system account for gravity, e.g.?Navigation systems are based on assumptions of initial state and perfect knoledge of g at every point. VLV
Reply by ●May 2, 20132013-05-02
Hi Randy, Am 01.05.13 22:22, schrieb Randy Yates:> Vladimir Vassilevsky <nospam@nowhere.com> writes: > >> On 5/1/2013 2:54 PM, Randy Yates wrote: >>> Looking for suggestions or pointers on how to track the gravity vector >>> in 6D data. >>> >> >> http://en.wikipedia.org/wiki/Equivalence_principle > > Hi Vlad, > > Thanks for that. Are you saying it's impossible? How does a navigational > system account for gravity, e.g.?AFAIK real systems use the Kalman filter to integrate the equations of motion (EOM). Googling for "kalman filter inertia" turns up lots of papers. A friend of mine once tried to integrate the EOM simply by discrete summing of the gravitational vector from his MacBook shock sensor. There was a large drift even only from walking down the hallway and back. Christian
Reply by ●May 2, 20132013-05-02
On Thu, 02 May 2013 09:23:54 +0200, Christian Gollwitzer wrote:> Hi Randy, > > Am 01.05.13 22:22, schrieb Randy Yates: >> Vladimir Vassilevsky <nospam@nowhere.com> writes: >> >>> On 5/1/2013 2:54 PM, Randy Yates wrote: >>>> Looking for suggestions or pointers on how to track the gravity >>>> vector in 6D data. >>>> >>>> >>> http://en.wikipedia.org/wiki/Equivalence_principle >> >> Hi Vlad, >> >> Thanks for that. Are you saying it's impossible? How does a >> navigational system account for gravity, e.g.? > > AFAIK real systems use the Kalman filter to integrate the equations of > motion (EOM). Googling for "kalman filter inertia" turns up lots of > papers. A friend of mine once tried to integrate the EOM simply by > discrete summing of the gravitational vector from his MacBook shock > sensor. There was a large drift even only from walking down the hallway > and back."Kalman" != "magic". Thus, a Kalman filter is not a magic filter, and is bound by the laws of physics. If all you have is inertial sensors, then the whole "Kalman filter" design exercise boils down to integrating the outputs of the inertial sensors in the obvious way. It does work, over a time span determined by the sensor accuracy. Sensors accurate enough to work on trips between continents are orders of magnitude more accurate (and more expensive) than anything you'll find inside an Apple product. Given inertial sensors _and_ some sort of external position fixes, such as GPS or other radio navigational aids, sightings of landmarks, or astronomical sightings, one can usefully develop a Kalman filter that is more than just a simple exercise in basic physical modeling. -- Tim Wescott Control system and signal processing consulting www.wescottdesign.com
Reply by ●May 2, 20132013-05-02
On Wed, 01 May 2013 16:22:31 -0400, Randy Yates wrote:> Vladimir Vassilevsky <nospam@nowhere.com> writes: > >> On 5/1/2013 2:54 PM, Randy Yates wrote: >>> Looking for suggestions or pointers on how to track the gravity vector >>> in 6D data. >>> >>> >> http://en.wikipedia.org/wiki/Equivalence_principle > > Hi Vlad, > > Thanks for that. Are you saying it's impossible? How does a navigational > system account for gravity, e.g.?Track how, and how accurately? If the motion you're dealing with isn't too severe you can get a pretty good estimate of "down" with a gyroscopically-stabilized average acceleration vector. Folks have been doing it since WW-II with mechanical gyros being servoed around by input from mercury tilt switches. -- Tim Wescott Control system and signal processing consulting www.wescottdesign.com
Reply by ●May 2, 20132013-05-02
Tim Wescott <tim@seemywebsite.please> writes:> On Thu, 02 May 2013 09:23:54 +0200, Christian Gollwitzer wrote: > >> Hi Randy, >> >> Am 01.05.13 22:22, schrieb Randy Yates: >>> Vladimir Vassilevsky <nospam@nowhere.com> writes: >>> >>>> On 5/1/2013 2:54 PM, Randy Yates wrote: >>>>> Looking for suggestions or pointers on how to track the gravity >>>>> vector in 6D data. >>>>> >>>>> >>>> http://en.wikipedia.org/wiki/Equivalence_principle >>> >>> Hi Vlad, >>> >>> Thanks for that. Are you saying it's impossible? How does a >>> navigational system account for gravity, e.g.? >> >> AFAIK real systems use the Kalman filter to integrate the equations of >> motion (EOM). Googling for "kalman filter inertia" turns up lots of >> papers. A friend of mine once tried to integrate the EOM simply by >> discrete summing of the gravitational vector from his MacBook shock >> sensor. There was a large drift even only from walking down the hallway >> and back. > > "Kalman" != "magic". Thus, a Kalman filter is not a magic filter, and is > bound by the laws of physics. > > If all you have is inertial sensors, then the whole "Kalman filter" > design exercise boils down to integrating the outputs of the inertial > sensors in the obvious way. It does work, over a time span determined by > the sensor accuracy. Sensors accurate enough to work on trips between > continents are orders of magnitude more accurate (and more expensive) > than anything you'll find inside an Apple product. > > Given inertial sensors _and_ some sort of external position fixes, such > as GPS or other radio navigational aids, sightings of landmarks, or > astronomical sightings, one can usefully develop a Kalman filter that is > more than just a simple exercise in basic physical modeling.Right. As I read, it seems the main use of Kalman filters is in Aided INS, in which there is some other information input to the filter besides the usual 6. -- Randy Yates Digital Signal Labs http://www.digitalsignallabs.com
Reply by ●May 2, 20132013-05-02
Tim Wescott <tim@seemywebsite.please> writes:> On Wed, 01 May 2013 16:22:31 -0400, Randy Yates wrote: > >> Vladimir Vassilevsky <nospam@nowhere.com> writes: >> >>> On 5/1/2013 2:54 PM, Randy Yates wrote: >>>> Looking for suggestions or pointers on how to track the gravity vector >>>> in 6D data. >>>> >>>> >>> http://en.wikipedia.org/wiki/Equivalence_principle >> >> Hi Vlad, >> >> Thanks for that. Are you saying it's impossible? How does a navigational >> system account for gravity, e.g.? > > Track how, and how accurately? If the motion you're dealing with isn't > too severe you can get a pretty good estimate of "down" with a > gyroscopically-stabilized average acceleration vector. Folks have been > doing it since WW-II with mechanical gyros being servoed around by input > from mercury tilt switches.Is 200G too severe? -- Randy Yates Digital Signal Labs http://www.digitalsignallabs.com
