Poorly conditioned Hessian matrix

Hello everyone, I am trying to simulate the impact that real group delay values could have on a gnss signal. clear all

N=50;

x=bocf2;

x=x(1:2001);%numel(x)=2001

F=[0:0.0005:1];%numel(F)=2001

b=abs(a);%numel(b)=2001

edges=[0 1];

[num,den]=iirgrpdelay(N,F,edges,b); The code demonstrated above is the one used for that reason.The values of b is of that magnitude -7.88E-08, -7.23E-08, -7.82E-08, -5.89E-08, -5.34E-08, -4.04E-08, The resulting error is this Warning: Matrix is close to singular or badly scaled. Results may be inaccurate. RCOND = 1.567922e-016. Error using iirgrpdelaymex Poorly conditioned Hessian matrix. Cannot accurately compute the optimization because either the approximation error is extremely small (try reducing the number of poles or zeros) or the filter specifications yield huge magnitude variations, such as mag=[1 1e9 0 0].

Error in iirgrpdelay (line 101) [as,tau]=iirgrpdelaymex(s.denOrd,s.edges,s.f,s.des,s.wt,...

Error in iirdelayskatapali (line 8) [num,den]=iirgrpdelay(N,F,edges,b); Could someone give me an explanation or an alternative?