Radar Tracking Software (using MATLAB)

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Presentation of Thesis …

Presentation of Thesis
by Charalambos Makris
for MSc Wireless Systems
Supervised by Dr. Peter Shepherd

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  • Hello and welcome to my presentation. My name is Charalambos and for today, I’ll be talking to you about my dissertation which is titled Radar Tracking Software.
  • We’ll begin the presentation with a description of the Radar used; then briefly talk about the purpose of the project and what it aims to achieve.The most part of the presentation will be spent on Input, Process and Output; importing, manipulating of radar data and displaying of images.Then the final outcome of the actual Software developed will be shown and some suggestions for future work/improvements will be given.Finally theconclusion will be drawn and if you have any questions about the project at the time, I’ll be happy to answer them.
  • In order to develop the Radar Tracking Software, we needed to find out how the radars work.For this project the Navtech Radar I-800, was used; from the picture you can see the actual radar, which is monostatic, meaning that it consists of a transceiver/ (both a transmitter and receiver), as opposed to other radar types which consist of separate modules for the transmitter and the receiver.Furthermore it uses Frequency Modulated Continuous Wave Technology at the frequency of 77GHz, which allows for millimetre accuracy, whilst the radar has a coverage range of 800m.Because the radar is continuously rotating at 360 degrees and collecting signals at a circular fashion, this means that it (has a theoretical coverage) can cover a distance of 1.6 kilometres.In order to read the radar data, both the NS-3 Navtech software had to be used as the interface that connects to the radar and the Radar Toolbox developed in MATLAB, slightly modified for the purposes of the project.
  • So what are the aims and objectives of the project?As the title suggests, we will develop a software which allows for the tracking of targets with the help of radars. Applications that can make use of such systems are endless, but the most common ones are used for monitoring, security and military purposes. This diagram demonstrates the sequence of events that are required, in order to achieve successful target tracking, all the way from the collection of data using the radar.These include the conversion of the raw data into signals as numbers, then formed into frames that make up a video sequence and finally, the targets must be separated from the background clutter/noise out of the movements within the video frames.To expand these processes slightly, I’ll explain them in more detail in the following slides.(We havethe radar which will be our equipment and we want to develop a software which can track and detect moving objects within the radar coverage area, referred to as targets.The targets cannot be detected straight from the radar but in fact, some processing is required beforehand.First the radar records the signals and saves them in a specific format as radar raw data and then this has to be converted into images so that they can be identified visually.At this point various filtering algorithms are used to reduce the clutter/noise that has been recorded alongside real objects within the raw data.The images are then processed in sequence in order to find the similarities and/or differences between consecutive frames and therefore allow for detection of targets)Radar: InputTargets: OutputIn between: Processing / image manipulation
  • The collection of data is done by powering on the radar and connecting its interface to a computer with NS-3 installed, in order to save the readings at the same time that they are collected by the radar.Then the Radar Toolbox is used to convert the .rpc format into .mat format which is readable by Matlab.Finally a modified version of the Radar Toolbox is used to save each frame into .png format, which saves the data as visible images, rather than just numbers in tables.
  • Just to demonstrate an example of the import process;This is an extremely simplified version of what the signal looks like in the form of a matrix,which when converted by the Radar Toolbox it looks like this.You can notice the scale legend and scale axis which appear in this frame, however I have modified the Radar Toolbox slightly to get rid of this, which results to a more natural image.Up to this point we have only prepared the frame to be in a format which can be manipulated by MATLAB.
  • Here are some algorithms which have been implemented within the software.If we only mention the important ones, the various Filters including Thresholding, used for each frame. From the complex algorithms all are equally important: Tracking & Detection of moving targets, Plotting and Trailing along their direction of travel and finally the prediction algorithms which calculate and extrapolate the expected travel path of the target.
  • The software which has been developed up to this point is not fully integrated;For certain functions processing is done automatically, but for some algorithms the user is required to intervene at different stages of the processing.Unfortunately even though the software gives correct results with the test images, it is not so successful with the real images and the code requires further debugging, as I’m still learning of how to program in MATLAB.The data flow diagram which follows, demonstrates the main flow of the final Radar Tracking Software.
  • Noise removal by including radar characteristicsPredicting to include spline interpolationto allow real time processingMore user friendly interface (GUI)Integration with: similar radars, surveillance cameras (CCTV, Infrared), Geo-location software (GPS device & map database)(enhancementsSuggest collaboration of many developers, each one responsible for implementing, improving a different functionality of the software.(Computer Science + Engineering Departments)
  • So in conclusion, the software needs several improvements in order to reach ??????????However, the implementation of a Radar Tracking Software is feasible with the use of MATLAB. More importantly however, it is relatively easy to code the necessary algorithms required for the radar frames, due to the Image Processing Toolbox integrated within MATLAB (and the extensive research & online community support). The Graphical User Interface Developing Environment also allows for of the design and implementation of a GUI for the software, with only a few limitations.
  • This is the end of my presentation, thank you for listening and now you can ask me any questions.

Transcript

  • 1. Radar Tracking SoftwareCharalambos MakrisSupervised by Dr. Peter Shepherd
  • 2. Contents• Introduction• Purpose• Input• Process• Output• Software• Future Work• Conclusions
  • 3. Hardware:Navtech I-800Radar• Monostatic• FMCW• 77GHz• 800m rangeSoftware:• NS-3• MATLABinterface,RadarToolbox(modified)Introduction
  • 4. PurposeRadar Signals Images Movement Targets
  • 5. Input• NS-3– Collect & Record radar raw data (.rpc)• Radar Toolbox– Convert raw data to frames matrices (.mat)– Save matrices as images (.png )• Radar Tracking Software– Save matrices in temporary memory
  • 6. Input• Radar data matrix• Radar Toolbox• Modified RadarToolbox
  • 7. ProcessSimple Algorithms• Flip / Rotate• Zoom / Crop• Filter– Average– Median– Threshold– MorphologicalComplex Algorithms• Detect– Logical Operators• Track• Plot• Trail• Forecast• Display frames
  • 8. Output• Moving target atconstant speedFrame 4Frame 7
  • 9. Output• Moving target atconstant speed– Plot– Trail– Predict
  • 10. Output• Target withaccelerating speedFrame 5Frame 8
  • 11. Output• Target withaccelerating speed– Plot– Trail– Predict
  • 12. Software• Some automatic functionality• Some algorithms as modules• User intervention• Real images: Code needs debugging• Test images: success
  • 13. Software (GUI)
  • 14. Data Flow Diagram (1/2)STARTImport radar data to MatlabStart reading radardata framesRead frameNext framePreviousFrameOlderFrameCurrentFrameRecord static objects
  • 15. Data Flow Diagram (2/2)DisplayYesNo Superimposeplots &trailsJoin related trailsClutter = AND [last 3 frames]Stationary Target = OR [last 3 frames]Moving Target = AND [current frame & 3 OR]Plot targetsSave new moving targetsAre new targetswithin acceptablevariation from old?
  • 16. Future Work• Improve algorithms for real radar data:– Noise removal– Predicting– Faster + more efficient, real-time• Implement seamless integration of allalgorithms• Allow user interference during processing• Selection of area of interest• Integration with parallel systems
  • 17. Conclusions• Currently dependingon Radar Toolbox forimporting raw data• Implementation usingMATLAB– Image ProcessingToolbox– GUIDE• Improvementsneeded• Radar TrackingSoftware developed– Various algorithmsimplemented• Track• Trail• Predict/Forecast
  • 18. Thank you for listening!