CIS115-6 Signals and Electronic Systems - University of Bedfordshire

Systems Engineering Assignment

Learning outcome 1: Demonstrate systematic understanding of advanced concepts of digital signal processing methods and systems engineering concepts, tools and techniques.

Learning outcome 2: Autonomously apply rigorous signal processing and systems engineering processes, implement solutions to selected problems with optimised performance and minimised risk and critically evaluate and present the results.

You are required to complete assignment referring to signal processing and systems engineering.

• Apply suitable methods analysed in class to the problem explained in the detailed brief.
• Explain the basic principles, as required in the detailed brief
• Present complex technical concepts in writing

Aim

• System design and analysis of antenna module for a Global Navigation Satellite System (GNSS) satellite

Task
You are working as a systems engineer at AntennaTech, a small-medium enterprise (SME) specialising in the custom design of hi-tech wireless systems.

The company encourages the use of formal systems design methodologies for new products as it is established through past experience that this approach enhances product success rate and increases customer satisfaction.

A client from the space communications sector has approached the company requiring facilitation in the design of a novel air-borne antenna for a new satellite to be launched soon as part of a specific GNSS. The client has the conceptual idea of the device along with its functional requirements and applications. However, he requires your company to develop the technical design of the product ready for manufacturing. You have been informed that the antenna module would be working as part of the navigation system of a satellite that would provide navigation and positioning services to commercial users worldwide.
Being leader of the systems design team, you are tasked to prepare the following two documents in order to facilitate the system design process:

1) Requirement Document
A formal requirement document is needed. The document should include:

a) Project Overview
Give a brief description of this project or product and its intended audience.

b) Product Context
Describe the general factors that affect the product and its requirements including:
i) Stakeholder Identification: Include a table providing brief description of each stakeholder, his role, needs and objectives.
ii) Assumptions: List any assumptions that affect the requirements.
iii) Constraints: List any items that will constrain the design options.
iv) Dependencies: List dependencies that affect the requirements.

c) Requirements
Describe all system requirements.
Organise these requirements in a way that works best for your project.
Describe every input into the system, every output from the system, and every function performed by the system in response to an input or in support of an output.
Each requirement should be numbered (or uniquely identifiable) and prioritized according to the following priority definition:
• Priority 1 - The requirement is a "must have" as outlined by policy/law.
• Priority 2 - The requirement is needed for improved processing, and the fulfillment of the requirement will create immediate benefits.
• Priority 3 - The requirement is a "nice to have" which may include new functionality.

i) User Requirements: List requirements of the system taking into account all the stakeholders.
ii) Functional Requirements: List the functional requirements of the system. Also include a Functional Flow Block Diagram of the system.

2) Risk Management Document
Perform a detailed risk assessment of the system and devise a plan to manage these risks. Summarise your findings in the form of a table providing risk description, type of the risk, consequences, risk level, and suggested control measure.

Signal Processing Assignment

Aim

• Gain experience of designing systems for image approximation using signal transforms

Task
You are designing an image compression method as a component of a new face recognition photography system. Your task is to design and optimise the image compression algorithm using the wavelet transform. Write a detailed individual report following the points below. For each task below, you need to provide a detailed justification for each choice you make.

A. Using only the operator symbols for filtering and downsampling, show and explain a detailed schematic diagram of the forward wavelet transform applied to images with only 1 decomposition level. Recall that the wavelet transform needs to be applied along horizontal and vertical directions when applied to images.

B. Using only the operator symbols for filtering and upsampling, show and explain a detailed schematic diagram of the inverse wavelet transform used for reconstruction of images with only 1 synthesis level.

C. Using the schematic diagram derived in A. as a building block, show and explain in detail the schematic diagram for deploying the forward wavelet transform with 3 iterations (decomposition levels) to images. Use the schematic diagram from A. as a box with input(s) and output(s) - there is no need to show again the content of the box.

D. Using the schematic diagram derived in B. as a building block, show and explain in detail the schematic diagram for the inverse wavelet transform using 3 iterations (decomposition levels).

E. Show a schematic diagram that combines the ones derived in C and D to apply image approximation. Assume that in the approximation process, all transform coefficients that do not belong to the lowest pass subband are set to zero.

F. Calculate how many operations (additions and multiplications) are required to be carried out for approximation (forward, then inverse wavelet transform with the modification as in E, that is zeroing out all the coefficients except the ones from the lowest pass subband) of an image of the size 512 x 512 pixels. Assume that the wavelet filters used in the process consist of 4 coefficients. Show and explain every step of the calculations. Show how the downsampling operator can reduce the number of operations.

G. Using the exercises and Matlab source code carried out in practicals, apply the approximation defined in F using one of the test images provided in Breo and calculate the mean-square error (MSE).

Attachment:- Signals and Electronic Systems.rar