**Part Number:** IWR1642

**Tool/software:** TI C/C++ Compiler

Hi,

I am learning people counting's gtrack.I have the following questions:

1.In the prediction step of EKF,

Q is the process noise covariance matrix.And we consider piecewise white noise model for the noise.

We define maxAcceleration 5m/s according to your demo.**What is the basis for setting the value?**

In gtrackUnitPredict function,obj.P_apriori(1:mSize,1:mSize) = obj.F(1:mSize,1:mSize) * obj.P(1:mSize,1:mSize) * obj.F(1:mSize,1:mSize)' + obj.Q(1:mSize,1:mSize)*obj.processVariance

processVariance = (0.5f*maxAcceleration)*(0.5f*maxAcceleration).Why is maxAcceleration multiplied by 0.5?

2.In gtrackUnitScore function,we compute the Mahalanobis distance between all measurements of cloud point and different tracks.

1)We build a gate using **gtrack_gateCreateLim** function.

gC_inv (EC) is the inverse of group covariance matrix(gC).Sometimes,the main diagonal of the matrix(gC_inv) is **negative** (gC's is positive).Is it right?Can the gate be negative?

2)

We use **gtrack_computeMahalanobis3** function to compute mahalanobis distance.Still,the main diagonal of the matrix(gC_inv) is sometimes **negative**.

Can the mahalanobis distance be negative?

Thanks,

Hanna