Improvements

Considering the achieved results, it can be understood that the radar demonstrator here presented, is well suited in targeting applications, such as, the ground based surveillance of stationary wide-zones and high security or hazardous infrastructures. The portability and compact size factor aid in this, allowing the radar to be easily and flexibly moved. The 24 channel, three-board FPGA based digital architecture, in conjunction with the MPC8640D based dual-core processor board, allows to easily process raw radar data, digitize it and transfer it to the software for the radar image processing. Additionally, the results from the radar digital signal processing and the delay and sum beam-forming, show good resolution and overall image reconstruction performance. The timing from capturing of a radar’s scenario to the generation of a radar image, is in total around 11 s, which does not allow the capturing of scenarios in the presence of moving targets. The main bottleneck of the system is the transferring of raw data through Ethernet to a binary file, which is consequently read into the radar beam-forming scripts. Addition- ally, the beam-forming is based on a delay and sum beam-former. All these aspects can be improved.

A study on this radar demonstrator, allowed to research the stages where improvements could be made, in order to address applications which require an even more compact and faster device, such as those linked to the detection of targets in flying platforms. Especially important, is the achievement of a system able to sense a complete 3D infor- mation of range, Azimuth and elevation of targets, even when these are moving.

Chapter 3. 3D Imaging FMCW MIMO Radar - 24 x 24 - Portable 84

Figure 3.49: _{dB - elevation, angular section view of the 3D radar image capture of} the target at 14 m and φ = −3◦_.

The ideas conceptualized into a reduction of the size factor of both the RF frontend, obtaining a single board with TX and RX antennas integrated, and the digital hardware architecture, obtaining a single board as well, which integrates a powerful ZYNQ based proprietary platform with all the ADCs. Furthermore, an implementation of a faster 3D-FFT based beam-forming processing is also achieved. These concepts will be seen in the next chapter.

Chapter 3. 3D Imaging FMCW MIMO Radar - 24 x 24 - Portable 85

Figure 3.50: _{dB - elevation, angular section view of the 3D radar image capture of} the target at 18.5 m and φ = −3◦_.

Figure 3.51: _{dB - elevation, angular section view of the 3D radar image capture of} the target at 22 m and φ = −1◦_.

Chapter 3. 3D Imaging FMCW MIMO Radar - 24 x 24 - Portable 86

Figure 3.52: _{dB - elevation, angular section view of the 3D radar image capture of} the target at 24 m and φ = −1◦_.

TARGET at 315 m

RADAR

Figure 3.53: _{The MIMO radar test field with one corner reflector at ranges of 315 m,} with nominal radar cross section of 36 m2

Chapter 3. 3D Imaging FMCW MIMO Radar - 24 x 24 - Portable 87

ZOOM

TARGET

Figure 3.54: _{Range-Azimuth section view of the 3D radar image capture, with 1} corner reflector visible at 315 meters.

Chapter 4

Multifunctional and Compact 3D

Imaging FMCW MIMO Radar

Demonstrator with 16x16

Antenna Array

4.1

Chapter’s Introduction

The previous chapter presented a successful implementation of a complete 3D imaging MIMO radar demonstrator, based on the transmit of FMCW signals from 16 GHz to 17 GHz with 1 GHz of bandwidth, multi-stacked PCB RF front-end, a TDM architec- ture, three FPGA boards plus a PowerPC enabled digital processing with a delay and sum beam-forming image generation.

In this chapter, a new MIMO radar system [140], result of a miniaturization and overall improvement in all aspects of the previous demonstrator, from the RF front-end, to the digital architecture and radar processing algorithms, is presented.

The idea is to obtain a system which can address applications linked, not only to the ground-based surveillance of stationary wide-zones and infrastructures, but also to the situational awareness and detection of targets in flying platforms, UAVs and helicopters. Therefore, the device has to be even more compact and have a faster and more perfor- mant radar processing. Especially important, is the implementation of a system able to detect targets even in moving environments and platforms and even when the targets themselves are moving, while still obtaining a complete 3D estimation of range, Azimuth and elevation of the targets. This leads to the development of a different architecture which is a first step towards the creation of a MIMO radar able to operate in an almost real-time manner, while still maintaining a small overall system cost and low hardware effort.

Moreover, an approach to combine an FMCW MIMO radar system with additional sen- sors and/or actuators, like a camera or a tracking system, introducing multiple functions, which are integrated in a single system, is also studied and analyzed. Therefore, the

Chapter 4. 3D Imaging FMCW MIMO Radar - 16x16 - Compact 90 term ”multifunctional” is used throughout this chapter, in order to address the fact that the system is able to perform more than just radar sensing.

The first step, is the achievement of a much smaller RF front-end, with a smarter an- tenna array configuration. Instead of multi-stacked PCBs and a modular approach, in the MIMO system presented in this chapter, a single planar PCB is used, which integrates 16 TX and 16 RX antennas, together with all the circuitry needed, from the amplifiers to the filters and mixers. The antennas used in the system presented in Chapter3, were TSA, which have now been replaced by narrow band patch antennas. A rectangular MIMO array with two rows of TX antennas and two rows of RX antennas, which are placed opposite to each other, offers an empty space in the center. This allows to integrate additional devices in the unused space, like a camera or a tracking system. Furthermore, a metallic 3D printed housing, which accomplishes also the task of cooling the electronics, has been built and assembled. Similarly to the previously presented MIMO radar system of Chapter 3, the orthogonality of the TX signals is obtained through TDM and the radar sensor working frequency range spans between 16 GHz and 17 GHz, using FMCW signals with 1 GHz bandwidth.

Additionally, a lot of research effort concretized into an achievement of a much faster digital architecture and signal processing, with yields a better performance. This is achieved due to the implementation of a new proprietary digital board, which integrates a lot of different functions, into a single device.

The board is based on a Xilinx ZYNQ Z-7045 SoC, a chip comprising two ARM CPU cores and FPGA fabric compatible to a Xilinx Kintex-7 FPGA [141]. Additionally, it is equipped with 16 ADC channels for the acquisition of the received radar signals. This SoC approach gives some degree of freedom to implement parts of the signal processing routines in hardware using the FPGA fabric and other parts in software using the ARM cores, as this way the computation of the radar data stream and the radar processing can be shared between domains.

An additional aspect where the system differs from the predecessor, is the new beam- forming and radar image processing. The system operates with a new 3D FFT based beam-forming at the RX side, which enables to capture radar images with a faster refresh rate, thus opening up the demonstrator to a multitude of additional radar applications, with moving scenarios or targets. The targeted applications are in accordance to the ones required by both the European project ”ZONeSEC” and the German project ”FAST”, for which part of the research has been focused to.

For this multifunctional system, a detailed descriptions of the hardware and software architecture, measurements, performance and resolution’s analysis, and 3D radar images are presented in this chapter.

The MIMO radar demonstrator is tested and analysed in several scenarios. In an ane- choic chamber and in outdoor test fields, for the detection of targets, both static and moving, represented by corner reflectors, UAVs and people.

Additionally, to show the advantages of a second functionality, the MIMO radar system is combined with a camera and a gimbal for target tracking. The imaging capabilities of the radar, integrated with the camera imaging capabilities, are presented for an outdoor test comprising trees and hills.

Chapter 4. 3D Imaging FMCW MIMO Radar - 16x16 - Compact 91 targets, and the target tracking capabilities of the system are analyzed. The detection is performed in the presence of UAVs and people.

Finally, a scenario where a jamming system, based on the MIMO radar demonstrator here discussed, is used against small UAVs, is also shown.