UWB ranging or localization using IEEE 802.15.4z

How to get the measurements with a random walk?

I know that the physical signal has added a random noise, but the measurements are same when I run some times. I simulate the physical measurements, they should be different in practice, How to solve it? I try to change the sigPower in awgn, but it does not work, the measurements are still same.

[praguna manvi]

Hi @Jun,

Can you be more specific about the simulation. See if this documentation helps :

https://www.mathworks.com/help/comm/ug/uwb-localization-using-ieee-802.15.4z.html

[Jun]

The measurement resolution is c/samplerare in the helperFindFirstHRPPreamble function. If the samplerare is 2GHz, the measurement resolution is 0.15m. For a range r=1 m. the measurent is 1.05 m, if there is a noise (0.12 m), the measurement is still 1.05 m. if there is a noise (-0.02 m), the measurement is still 1.05 m. The noise is invalid.

Is measurement resolution correct? Or I need to optimized the measurement resolution by interpolation?

[Supraja]

Hello,

To generate the signal, follow the points mentioned below:

1. Random Seed Initialization: To ensure different noise in each run, initialize the random number generator with a changing seed, such as based on the current time. This prevents the same sequence of random numbers from being generated every time.

2. AWGN Function: To add noise with a specific power, manually scale the Gaussian noise to match the desired noise power before adding it to your signal. This gives you direct control over the noise characteristics.Please find the documentation of the function below: https://in.mathworks.com/help/comm/ref/awgn.html

3. Random Walk: Simulate a random walk by generating random steps and calculating their cumulative sum. This can be added to your signal to model a gradual drift or fluctuation over time. Please find the documentation link of cumsum function below: https://in.mathworks.com/help/matlab/ref/double.cumsum.html

These steps help manage randomness in simulations, balancing variability and repeatability as needed.