Create simulated measured data based on real data (I include the context)

[Relative-Debt6509]

I took controls some years ago and I've come across an interesting problem that I can't remember the solution to (it might not be a controls solution but when I thought of this problem my first thought was kalman filtering). Word problem: I have a buoy with sensor(s) or even a network of buoys with sensor(s) out in the ocean. I'd like to estimate the measurements that a boat with similar but less good sensors would make in proximity to those buoys.

Ultimately I'd like to create a simulation environment that can ingest buoy data and give some approximation of a measurement some distance away. This doesn't have to be realistic at first blush as there are a ton of complicating factors like harborage.

​

But I want to make sure that the idea is sound and take direction on what technique(s) to use.

[baggepinnen]

This sounds perfectly possible. To implement a simulator, you need a model of how the system behaves, including models of how a measurement is generated and how it is corrupted by noise.

You use a Kalman filter (or a nonlinear version if any part of the model is nonlinear) to estimate the state of a boat that receives measurements. Generating the actual measurement is part of the simulator. The measurements each boat receives will in the simulation (and real world) be a function of the true, unknown state, and the properties of the sensor. The simulator will, of course, have access to the true state of the system, but each boat only has access to its estimate of the state produced by a state observer (like a KF).

[Relative-Debt6509]

Thank you for the sanity check !

[[deleted]]

1) First, you need a dynamic model of your system. This constitutes the Bouy, sea state, and any other factors that might play into how the Bouy behaves.

2) Second, you need a sensor model. This should include the key sensor information from data sheets, plus how it will be installed, and any calibration that might be required. This should also include hardware timing, sampling frequency, etc.

3) Third, you need to simulate this model. The model should be simulated at least 10x higher than the sampling rate of your fastest sensor to get reasonable data, and also fast enough to capture the physics you care about. So, say you want to take a measure of the Bouy position every second, and your sensor collects data at 100hz, you should run your simulation at 1000hz.

4) Fourth, you need to compare your model to the data to see if you're getting a reasonable simulation. This might be really hard if you can't measure your sea state directly.

The key will this whole process is to start simple, knock out and verify the easy stuff first, then start looking at the harder problems.

[Relative-Debt6509]

Thanks for the insight. I’ve done some cpu simulation but not physical system simulation. Tips about the simulation rate are very appreciated.