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During 2021 we will continue to support students who need to study remotely due to the ongoing impacts of COVID-19 and travel restrictions. Make sure you check the location code when selecting a unit outline or choosing your units of study in Sydney Student. Find out more about what these codes mean. Both remote and on-campus locations have the same learning activities and assessments, however teaching staff may vary. More information about face-to-face teaching and assessment arrangements for each unit will be provided on Canvas.

Unit of study_

MECH5720: Sensors and Signals

Syllabus Summary: This course starts by providing a background to the signals and transforms required to understand modern sensors. It goes on to provide an overview of the workings of typical active sensors (Radar, Lidar and Sonar). It provides insight into basic sensing methods as well as aspects of interfacing and signal processing. It includes both background material and a number of case studies. The course covers the following topics: a) SIGNALS: Convolution, The Fourier Transform, Modulation (FM, AM, FSK, PSK etc), Frequency shifting (mixing) b) PASSIVE SENSORS: Infrared Radiometers, Imaging Infrared, Passive Microwave Imaging, Visible Imaging and Image Intensifiers c) ACTIVE SENSORS THE BASICS: Operational Principles, Time of flight (TOF) Measurement and Imaging of Radar, Lidar and Sonar, Radio Tags and Transponders, Range Tacking, Doppler Measurement, Phase Measurement d) SENSORS AND THE ENVIRONMENT: Atmospheric Effects, Target Characteristics, Clutter Characteristics, Multipath e) ACTIVE SENSORS: ADVANCED TECHNIQUES: Probability of Detection, Angle Measurement and Tracking, Combined Range/Doppler and Angle Tracking, Frequency Modulation and the Fast Fourier Transform, High Range Resolution, Wide Aperture Methods, Synthetic Aperture Methods (SAR) Objectives: The course aims to provide students with a good practical knowledge of a broad range of sensor technologies, operational principles and relevant signal processing techniques. Expected Outcomes: A good understanding of active sensors, their outputs and applicable signal processing techniques. An appreciation of the basic sensors that are available to engineers and when they should be used.


Academic unit Aerospace, Mechanical and Mechatronic
Unit code MECH5720
Unit name Sensors and Signals
Session, year
Semester 2, 2021
Attendance mode Normal day
Location Camperdown/Darlington, Sydney
Credit points 6

Enrolment rules

MTRX3700 or MTRX3760
Assumed knowledge

Strong MATLAB skills

Available to study abroad and exchange students


Teaching staff and contact details

Coordinator Graham Brooker,
Lecturer(s) Graham Brooker ,
Tutor(s) Jacob MacKay ,
Type Description Weight Due Length
Final exam (Open book) Type C final exam hurdle task Final exam
Type C
30% Formal exam period 2 hours
Outcomes assessed: LO1 LO6 LO5 LO4
Tutorial quiz MATLAB tutorial
Matlab-based analysis
20% Multiple weeks 2 hrs in tutorial plus additional time
Outcomes assessed: LO4 LO5 LO7
Small test Post-lecture Quizzes
Quiz to be completed after each lecture to assist with consolidation
13% Multiple weeks Typically 30 to 60 minutes
Outcomes assessed: LO1 LO7 LO6 LO5 LO4
Tutorial quiz Laboratory
Quiz to be completed after each laboratory session.
22% Multiple weeks 3 hrs in Lab plus 3 hrs post-Lab
Outcomes assessed: LO3 LO4 LO5
Creative assessments / demonstrations Assignment
Research and design assignment ongoing
15% Week 12 n/a
Outcomes assessed: LO1 LO2 LO3 LO4 LO5 LO6 LO7
hurdle task = hurdle task ?
Type C final exam = Type C final exam ?
  • MATLAB tutorial: A number of hands-on tutorials will be undertaken during which students are expected to apply and investigate what they have learned by developing models and software.
  • Quizzes: A quiz will be held after each lecture to ensure that students have understood the work covered so far.
  • Lab activities: Weekly individual in-person (on campus students) or online (off camuus students) activities during which students will be required to assemble sensing, processing, and actuation hardware that illustrates sensing and signal processing concepts.
  • Assignment: The individual design assignment will be based on ongoing work done by the students to develop ideas for a sensing device in stages throughout the first half of the semester as their knowledge and understanding of the subject develops.
  • Final exam: Open-book examination that will include a number of short-answer questions. Students are required to pass the exam to pass the unit.

Detailed information for each assessment task can be found on Canvas.

Assessment criteria

The University awards common result grades, set out in the Coursework Policy 2014 (Schedule 1).

As a general guide, a high distinction indicates work of an exceptional standard, a distinction a very high standard, a credit a good standard, and a pass an acceptable standard.

Result name

Mark range


High distinction

85 - 100



75 - 84



65 - 74



50 - 64



0 - 49

When you don’t meet the learning outcomes of the unit to a satisfactory standard.

For more information see

Late submission

In accordance with University policy, these penalties apply when written work is submitted after 11:59pm on the due date:

  • Deduction of 5% of the maximum mark for each calendar day after the due date.
  • After ten calendar days late, a mark of zero will be awarded.

This unit has an exception to the standard University policy or supplementary information has been provided by the unit coordinator. This information is displayed below:

25% per day (or part thereof) to minimise student collusion

Special consideration

If you experience short-term circumstances beyond your control, such as illness, injury or misadventure or if you have essential commitments which impact your preparation or performance in an assessment, you may be eligible for special consideration or special arrangements.

Academic integrity

The Current Student website provides information on academic honesty, academic dishonesty, and the resources available to all students.

The University expects students and staff to act ethically and honestly and will treat all allegations of academic dishonesty or plagiarism seriously.

We use similarity detection software to detect potential instances of plagiarism or other forms of academic dishonesty. If such matches indicate evidence of plagiarism or other forms of dishonesty, your teacher is required to report your work for further investigation.

WK Topic Learning activity Learning outcomes
Week 01 Modulation (2 hr) LO1 LO4
Measure Foundry Introduction (3 hr) LO1 LO4 LO5
Week 02 Filtering and Modulation (2 hr) LO1 LO4 LO5
Measure Foundry - Graphs, Filtering & FFT (3 hr) LO1 LO4 LO5
Week 03 Active Ranging Sensors (2 hr) LO1 LO3 LO4 LO5 LO6 LO7
Modulation (1 hr) LO4
Measure Foundry - Pulsed Sonar (3 hr) LO1 LO4 LO5
Week 04 Active Imaging Sensors (2 hr) LO1 LO4 LO5 LO6 LO7
Modulation (1 hr) LO4
Measure Foundry - Tellurometer Sonar (3 hr) LO1 LO4 LO5
Week 05 Signal Propagation (2 hr) LO4 LO7
3D Imaging (1 hr) LO4
Measure Foundry - Attenuation (3 hr) LO1 LO4 LO5
Week 06 Target Detection in Noise (2 hr) LO1 LO4 LO7
3D Imaging (1 hr) LO4
Measure Foundry - Multipath (3 hr) LO1 LO4 LO5
Week 07 Target and Clutter Characteristics (2 hr) LO1 LO3 LO4 LO7
Radar Range Equation (1 hr) LO4
Measure Foundry - RCS with Angle (3 hr) LO1 LO4 LO5
Week 08 Doppler Processing (2 hr) LO4 LO5 LO6 LO7
Radar Range Equation (1 hr) LO4
Measure Foundry - RCS with Angle (3 hr) LO1 LO4 LO5
Week 09 High Angular Resolution Sensors (2 hr) LO1 LO3 LO4 LO5 LO6 LO7
Matched Filter & Doppler (1 hr) LO4
Measure Foundry - Phased Array Sonar (3 hr) LO1 LO4 LO5
Week 10 High Range Resolution Sensors (2 hr) LO1 LO3 LO4 LO5 LO6 LO7
Matched Filter & Doppler (1 hr) LO4
Measure Foundry - Phased Array Sonar (3 hr) LO1 LO4 LO5
Week 11 Range and Angle Estimation (2 hr) LO1 LO3 LO4 LO5 LO6 LO7
Phased Arrays (1 hr) LO4
Measure Foundry - Antenna Transfer Function and Tracking (3 hr) LO1 LO4 LO5
Week 12 Tracking Moving Targets (2 hr) LO1 LO3 LO4 LO5 LO6 LO7
Phased Arrays (1 hr) LO4
Measure Foundry - Antenna transfer Function and Tracking (3 hr) LO1 LO4 LO5
Week 13 Radiometry (2 hr) LO1 LO4 LO6 LO7
Weekly Students are expected to commit to at least 5 hours per week of independent study in addition to timetabled activities. (65 hr) LO1 LO2 LO3 LO4 LO5 LO6 LO7

Attendance and class requirements

  • Project work (own time): A design project will be undertaken by groups of students. This will take the form of research conducted by each student during the semester as their knowledge of the subject improves. Towards the end of semester each student will compile an individual design report which will be assessed by the lecturer.
  • Independent study: Depending on student competence and background, at least five hours of private study per week outside formal contact hours will be required to consolidate the work covered in class.
  • Laboratory: Student groups will assemble and measure the characteristics of various sensors. Some Measure Foundry code will be provided but students will be expected to develop additional code. Laboratory sessions may be in-person (on campus students) or online (off campus students).
  • Tutorial: A number of MATLAB tutorials will be undertaken, during which students are expected to develop code to model some sensing or signal processing application.

Study commitment

Typically, there is a minimum expectation of 1.5-2 hours of student effort per week per credit point for units of study offered over a full semester. For a 6 credit point unit, this equates to roughly 120-150 hours of student effort in total.

Required readings

All readings for this unit can be accessed through the Library eReserve, available on Canvas.

  • Graham Brooker, Introduction to Sensors for Ranging and Imaging. Scitech Publishing, 2008. 9781891121746.

Learning outcomes are what students know, understand and are able to do on completion of a unit of study. They are aligned with the University’s graduate qualities and are assessed as part of the curriculum.

At the completion of this unit, you should be able to:

  • LO1. assimilate information regarding the myriad of possibilities for the design of a sensor, and to convey this information to ones colleagues
  • LO2. develop skills for efficient project management in a team environment
  • LO3. integrate incomplete information and make value judgements to solve a sensing problem by using engineering "gut feel", rather than a rigorous analytical approach
  • LO4. apply specialised engineering skills (mechanical, electrical, and software) to analyse the performance of a sensor
  • LO5. understand active sensors, their outputs, and applicable signal processing techniques, and demonstrate an appreciation of the basic sensors that are available to engineers, and when they should be used
  • LO6. describe a number of sensors
  • LO7. make a distinction between sensor performance, based on simulation and measurement.

Graduate qualities

The graduate qualities are the qualities and skills that all University of Sydney graduates must demonstrate on successful completion of an award course. As a future Sydney graduate, the set of qualities have been designed to equip you for the contemporary world.

GQ1 Depth of disciplinary expertise

Deep disciplinary expertise is the ability to integrate and rigorously apply knowledge, understanding and skills of a recognised discipline defined by scholarly activity, as well as familiarity with evolving practice of the discipline.

GQ2 Critical thinking and problem solving

Critical thinking and problem solving are the questioning of ideas, evidence and assumptions in order to propose and evaluate hypotheses or alternative arguments before formulating a conclusion or a solution to an identified problem.

GQ3 Oral and written communication

Effective communication, in both oral and written form, is the clear exchange of meaning in a manner that is appropriate to audience and context.

GQ4 Information and digital literacy

Information and digital literacy is the ability to locate, interpret, evaluate, manage, adapt, integrate, create and convey information using appropriate resources, tools and strategies.

GQ5 Inventiveness

Generating novel ideas and solutions.

GQ6 Cultural competence

Cultural Competence is the ability to actively, ethically, respectfully, and successfully engage across and between cultures. In the Australian context, this includes and celebrates Aboriginal and Torres Strait Islander cultures, knowledge systems, and a mature understanding of contemporary issues.

GQ7 Interdisciplinary effectiveness

Interdisciplinary effectiveness is the integration and synthesis of multiple viewpoints and practices, working effectively across disciplinary boundaries.

GQ8 Integrated professional, ethical, and personal identity

An integrated professional, ethical and personal identity is understanding the interaction between one’s personal and professional selves in an ethical context.

GQ9 Influence

Engaging others in a process, idea or vision.

Outcome map

Learning outcomes Graduate qualities
This unit is mature, so the only changes made have been in response to COVID-19. This has resulted in the development of some online labs.

Work, health and safety

Details of the WHS requirements for in-person laboratory sessions during the COVID-19 pandemic are available on Canvas.



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