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I've been working on a project where I'm supposed to design a vehicle that carries antennas to perform SAR (Synthetic-aperture radar) imaging. This vehicle has 3 wheels which 2 of them steered by a DC motor. In order to accurately perform SAR imaging algorithm, I need to know how much my car moved from its last location. There are several methods I've looked up so far, However there are problems with each of that:

  • GPS: Using GPS, I can do some calculations to see how much my car moved. However, since GPS locations are off about 4-5 meters, calculations that I'll make won't be accurate at all.

  • Ultrasonic Sensor: The problem about this way is limited distance range. (As I know 5-10 meters)

  • Accelerometer: Even though it seems mathematically possible to calculate distance traveled using instant acceleration, the errors occurring over time makes this calculation meaningless. There are some proposed ways like Kalman filtering to increase accuracy of these calculations.

  • Computer Vision: Using CV, I can track something on the vehicle and calculate its distance from the camera. I don't have much experience about this, therefore I can't estimate its accuracy.

  • Encoder: This way consists an encoder to track how much the wheels have turned. This seems to be a good way however I don't know if I can be accurate with this method.

I'm aiming for at least ±5cm accuracy. The total distance may reach dozens of meters.

In above ways or others, what would be a good possible solution to overcome this?

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    \$\begingroup\$ With enough integration time and phase analysis you can get down gps to cm accuracy. \$\endgroup\$
    – PlasmaHH
    Oct 9, 2018 at 12:41
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    \$\begingroup\$ The unspoken question in Plasma's comment is: how much time do you have to get a location fix? \$\endgroup\$ Oct 9, 2018 at 13:44
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    \$\begingroup\$ If you wheels are hard rubber and have a differential radius error compensation to 0.01% from test and calibration, you can get 1mm short term resolution with quadrature wheel encoders and then GPS for long term re-sync with IR to detect objects near your for collision avoidance, then and create a cookie trail for returning back storing waypoints for positions. Golf carts might use Differential GPS with a local Tx to improve response integration time and resolution \$\endgroup\$ Oct 15, 2018 at 16:49
  • \$\begingroup\$ @TonyEErocketscientist This was the idea that I come up to. Could you please post this comment as an answer? \$\endgroup\$
    – Şener
    Oct 16, 2018 at 6:24
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    \$\begingroup\$ This is a solved problem. I suggest going to the engineering literature to find out what the state of the art is -- at least the non-proprietary portions. I suspect it will tell you that the working models use a combination of most of the techniques you've listed. \$\endgroup\$ Oct 16, 2018 at 16:34

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1) Calibrated Odometer method with GPS sync

Car Speedometers and odometers are often inaccurate due to choices with oversized tires. But with on-board computers and some calibration routine , it is theoretically possible to get high accuracy. The integration of this error must be specified by your system specs.

You must start with an error budget and allocate in parts per million xxx ppm for each source of error: mfg tolerance , tire, wear , cornering slip, loose surface grip, brake skids, elevation changes in Z axis.

Then determine when resync is needed with GPS. Keeping a rolling history of cumulative Position Error , forever, for create an algorithm for forward error correction from each of these above error budget sources. Then create Forward Predictor Correction factors for each cause to reduce the need to resync with GPS.

It may depend on your accuracy tolerance, and integration time response specs to determine the optimal trade off between quadrature dual wheel incremental encoders and GPS . Compute the sensitivity to errors if you wish to find the opportunities for improvement.

Always start with good specs with assumptions then verify, improve and repeat until ok.

2) Alternatively, if you rely on a mobile with MEMs accelerometer, Gyro and GPS, and just use an SDK to interface to the API , then it becomes a selection process and software needs starting again with a MODIFIED spec.

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