Filter Practice Problem for P.E. Exam, HELP

[AlexMarshall]

Hey everyone, I'm trying to get prepped from my EE Professional Engineering exam and there is a question that I cannot solve in the prep-guide. I'm hoping that someone might be able to help because it can be solved in MatLab (as noted in the book). Here is the problem description:

You are an engineer working at a major automotive manufacturer that offers a back-up/obstacle-detection system using sensors installed in the rear bumper. The sensors emit an ultrasonic signal ranging from 40-50 KHz. When an object is present, some of the ultrasonic signal is reflected back and the system will alert to driver to the obstacle. In minimal signal required for this detection is -70dBuV. The amplitude of the returned signal is indicative of the object's size.

Alongside the system, there is an electronic module radiating noise at 75 KHz. The level of this noise can be as high as -60dBuV. In order for this back-up system to function properly, the noise must be 15 dB below the desired signal. Note that the impedance and load impedance is 50 Ohms.

Problem:

Part A. Design an analog filter that will eliminate the impact of the noise on the system in a cost effective manner. Note any impacts that the filter may have on the back-up system.

Part B. Implement an Infinite Impulse Response (IIR) digital filter based on the analog filter in Part A. [Utilize MatLab]

Part C. Implement a Finite Impulse Response (FIR) digital filter that will eliminate the impact of the noise on the system. [Utilize MatLab]

Here is what I know thus far:

For Part A, I've located in the P.E. Reference manual the following instructions:

Create an Analog Filter
1. Transform to a low pass filter so that Filter Tables can be used
2. Normalize the Filter
3. Select the Filter Type
4. Determine the Filter Order
5. Establish T(s)
6. Verify T(s) by plotting the magnitude of T(j*omega)
7. Unnormalize Transform
8. Verify Unnormalized Transform by plotting magnitude of T(j*omega)

For Part B and C, I've narrowed it down to using the filter design tools to design a bandpass filters with pass band 40-50 kHz with no more than -25dB response at 75 kHz. I'm not sure if this is correct though.

I've located the following resources online but do not understand how to apply them towards my example.

http://www.mikroe.com/eng/chapters/view/73/chapter-3-iir-filters/
http://www.mathworks.com/help/toolbox/signal/ref/lp2bs.html

I really appreciate any help that you all would have to offer! This is the one problem that I haven't been able to solve in the manual!

Thank you!

 

[AlexMarshall]

Hey Everyone, I put together the following code but I'm stuck! Please see below!

f_p=40000; %Pass Frequency in Hz

f_s=50000; %Stop Frequency in Hz

r_s=25; %Stopband Attenuation in dB

r_p=3; %Passband Ripple

d = fdesign.bandpass('Fst1,Fp1,Fp2,Fst2,Ast1,Ap,Ast2', 38e3,f_p,f_s,53e3,r_s,r_p,140e3);

%Fst1 — frequency at the edge of the end of the first stop band. Specified in normalized frequency units by default.

%Fp1 — frequency at the edge of the start of the pass band. Specified in normalized frequency units by default.

%Fp2 — frequency at the edge of the end of the pass band. Specified in normalized frequency units by default.

%Fst2 — frequency at the edge of the start of the second stop band. Specified in normalized frequency units by default.

%Ap — passband ripple in dB (the default units).

%Ast1 — attenuation in the first stopband in dB (the default units).

%Ast2 — attenuation in the second stopband in dB (the default units).

% Create the FIR filter

Hd2 = design(d,'equiripple'); fvtool(Hd2)

%Create the IIR filter

Hd1 = design(d,'butter'); fvtool(Hd1);

------------------------------------------------------------------

First off, does my methodology seem correct for creating an FIR and IIR filter that will accomplish this goal? Secondly, when I run the code, this is the error message I get:

? Error using ==> fdesign.abstracttype.equiripple at 13 Frequency specifications must be between 0 and 1.

Error in ==> fdesign.abstracttype.superdesign at 106 Hd = feval(method, this, varargin{:});

Error in ==> fdesign.abstracttype.design at 11 varargout{1} = superdesign(this, varargin{:});

Error in ==> PEPractice at 13 Hd2 = design(d,'equiripple');

-----------------------------------------------------------------

Any insight as to what is wrong? Please help if you can!

 

[AlexMarshall]

I found the error, the correct d should be:
d = fdesign.bandpass('Fst1,Fp1,Fp2,Fst2,Ast1,Ap,Ast2',38e3,f_p,f_s,53e3,r_s,r_p,r_s,140e3);

Okay, so now that it compiled, I've ran into some concerns. For one thing, how can I tell if this is right and if it meets the problem description? I know it has something to do with checking the levels (magnitudes) in the amplitude response.

Please help if you can!

 

[berkeman]

Welcome to the PF.

For part A, it seems like a lowpass filter (LPF) would work. Is there a reason that you want to use a bandpass filter? For about the same number of components, you get twice the rolloff with a LPF compared to a BPF.

Here is an analog filter tutorial/wizard from TI that may be helpful:

http://www-k.ext.ti.com/SRVS/Data/ti/KnowledgeBases/analog/document/faqs/filter.htm

.

 

[DeeNos]

Hello,

I can understand your frustration with this problem, but don't worry, I'm here to help. I have experience in designing and implementing filters for various applications.

For Part A, your approach seems to be on the right track. You will need to design a low pass filter that can eliminate the noise at 75 kHz while still allowing the desired signal at 40-50 kHz to pass through. In order to do this, you will need to determine the filter type and order, as well as the transfer function T(s) for your filter. This can be done using various filter design methods, such as Butterworth, Chebyshev, or Elliptic filters. Once you have designed your filter, it is important to verify its performance by plotting the magnitude of T(j*omega) to ensure that the desired signal is not affected.

For Part B and C, you will need to implement a digital filter based on your analog filter design. This can be done using the filter design tools in MatLab. You will need to specify the pass band and stop band frequencies, as well as the desired attenuation at the stop band. The resulting filter will be an IIR (infinite impulse response) filter, which means it will have feedback loops and can provide better performance than FIR filters.

For Part C, you will need to design a FIR (finite impulse response) filter. This type of filter does not have feedback loops and is typically used for applications where linear phase response is desired. Again, you can use the filter design tools in MatLab to design your FIR filter based on the specifications given in the problem.

I would also recommend checking out the resources you have found online, as they can provide helpful information and examples on how to design and implement IIR and FIR filters.

I hope this helps and good luck on your exam! Remember to always verify the performance of your filters to ensure they are meeting the desired specifications.