Memsense nano IMU

gyroimu

I am using Memsense nano IMU and specifically i am interested in getting the three axes Gyroscope data out of its 38 bytes frames. Following are the snapshots of the frames, and collected gyro data for x,y and z axes (16 bits each) (when the IMU is stand still):

IMU_Frame_with_headers
Gyro_rate_x_axis
Gyro_rate_y_axis
Gyro_rate_z_axis

Now even if i remove the bias from these gyro rate values, the values are too random and nonsense. In fact i tried to integrate them to get the angles too but i could not get them correctly.

Is this a normal behavior we can expect out of these sensors or there is some malfunctioning on the part of my IMU?

Moderators:I have checked the other posts related to IMUs and gyro problems but i could not find this basic discussion.

Best Answer

You didn't say which model of IMU you got.

For the -1200F050 model, the datasheet indicates that the gyro noise level (one σ) is 0.56°/s typical, and given that the sensitivity is 0.055°/s/count, that would give you a noise level that hovers around 10 counts.

For the -0150F050 model, the noise level (one σ) is 0.36°/s typical, and given that the sensitivity is 0.0068°/s/count, that would give you a noise level that hovers around 53 counts.

I didn't analyze your data, since you didn't provide it in copyable form, but those numbers look about right (including bias) for the more sensitive model.

ADDITIONAL

Keep in mind that the noise specification is a statistical measurement. The noise is assumed to be "additive white Gaussian noise" (AWGN), and the level is given as a one-sigma (σ) value, which is a standard way of characterizing a Gaussian distribution (the standard deviation). You can think of this as a kind of RMS value; it's equivalent to specifying the noise power when you're talking about voltage or current.

What this means is that 68.2% of the time (68.2% of the samples) will have a noise value that's less than the specified number (53 counts in this case). The rest of the time, the value can be larger — in some cases, much larger.

If you want to get a better idea of what you might consider to be a "peak" value fore the noise, you need to look at the 3σ value — 99.8% of the time, the noise in a sample will be less than 3 × 53 = 159 counts.

If you can provide your data in machine-readable format, it's very straightforward to calculate its mean and standard deviation to see whether it matches the sensor specifications. I suspect that it's well within spec.

INTEGRATION

When you integrate a value that has both a bias error term and a noise term, the result will wander away from the correct value even if the underlying "signal" is zero. The bias term (essentially a constant), when integrated, becomees a linear "ramp", which means that the error grows linearly with time. The noise term, when integrated, becomes a "random walk", and the output error associated with this grows proportionally to the square root of the integration time.

Unless you can find a way to compensate for these errors (using data from other sensors), the result will become useless within minutes or even seconds, depending on the quality of the sensor.

Related Solutions

Electronic – Magnetometer dynamic calibration

I like your graphs. They clearly show that roll, pitch, and yaw seem to be working. Congratulations! That's already more progress than most people make.

I'm guessing that the code you presented is calculating "the wrong" MAG_Heading value, different from the MAG_Heading value you expected.

It would be a lot easier for us to help you if you gave us: (This is the "describe the symptoms" section of "How To Ask Questions The Smart Way" )

the AK8975 magnetometer output values m_x, m_y, and m_z at some single point in time.
The pitch and roll values at the same instant
the allegedly wrong MAG_Heading output value calculated from those values
what you expected the correct MAG_Heading to be

So I'm left to speculate that perhaps you're running into the same sorts of problems I create for myself :-).

What angle format do your sin() and cos() and atan2() functions expect? Do you need to do some sort of conversion between the format pitch and roll are stored in to that format? Do you need to convert from that format to what you need MAG_heading? (brads, degrees, or radians? floating-point or fixed-point?)
Is there an offset in the raw m_x, m_y, m_z values that needs to be subtracted off?
Are all the parts lined up in the way assumed by the code? In particular, is the pitch and roll axis lined up with the magnetometer axis? (Is m_x supposed to point forward, along the roll axis? Is m_y supposed to point to the right, along the pitch axis?)
Maybe some sensor value or another -- perhaps m_z -- needs to be negated before feeding into this code?
Is maybe this code being interrupted by one interrupt or another that corrupts its internal values? I seem to recall a different project that, after someone put a "divide" in an interrupt routine, every trig function calculation everywhere else in the program would often give the wrong result.
Is maybe interrupts firing so often that this code never actually finishes running?

There seems to be other people discussing very similar code elsewhere: http://diydrones.com/forum/topics/heading-from-3d-magnetometer ; http://diydrones.ning.com/profiles/blogs/dcm-imu-theory-first-draft ; http://aeroquad.com/showthread.php?1138-REVOLUTION!!!-New-IMU!!! ; http://www.rcgroups.com/forums/showthread.php?t=1436742&page=6 ; http://aeroquad.com/showthread.php?691-Hold-your-heading-with-HMC5843-Magnetometer ; etc.

Electronic – L3G4200D Gyro Sensor – Measuring Angle

First, you could use something like this to get your value into a proper signed integer:

uint8_t xl = ...;
uint8_t xh = ...;
int16_t x = *(int8_t *)(&xh);
x *= (1 << 8);
x |= xl;

But x is just a value in Degree per Second. To get your current orientation as angle, you have to integrate this value over time, which will add a lot of drift. To compensate for this, you could then filter it with accelerometer data (PDF!).

Best Answer

Related Solutions

Electronic – Magnetometer dynamic calibration

Electronic – L3G4200D Gyro Sensor – Measuring Angle

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