MIMO radar Systems and Algorithms - Imperfections and Calibration

Drones, also known as Unmanned Airborne Vehicles (UAVs), offer unique and economical solutions for countless applications within a large variety of industries such as delivery and agriculture. Unfortunately, drones are also considered a high threat in terms of security and defence due to their size and manoeuvrability, making them challenging to detect. Radars offer the capabilities necessary for drone detection, tracking, and classification, making it one of the preferred systems for the task. The Multiple-Input Multiple-Output (MIMO) radar consists of a transmitting and receiving array, where waveform separation forms a well-defined virtual array from all transmit and receive channel combinations. The concept offers continuous monitoring within a large field-of-view with an enhanced angular resolution compared to the number of physical elements. These advantages make the MIMO radar attractive for drone detection, extending the possibilities for multi-target tracking. However, to ensure a high probability of detection, system imperfections are to be considered. They will either affect a system as channel imbalance or mutual coupling. Channel imbalance refers to undesired amplitude and phase variations across the array of channels, while mutual coupling occurs when channels affect each other. Because every physical transmit and receive channel is combined, the imperfections of a single channel become present multiple times in the virtual array. Hence, without proper MIMO radar calibration, system imperfections can cause severe performance degradation. This will be the primary objective of this dissertation, where the impact on the MIMO radar performance is investigated, together with calibration techniques suitable for MIMO radar. A novel measurement-based technique to estimate suitable calibration coefficients of a MIMO system is presented. It exploits that several independent measurements of each channel are obtained with a single MIMO measurement prior to processing the angular information. A theoretical study of waveform separation on the received signal applicable to MIMO systems is included to assess the various possibilities for successfully forming the virtual array. Additionally, direction-of-arrival estimation techniques are investigated and applied to the virtual array for determining the directions of the received  signals. Experimental data is acquired with an X-band MIMO radar demonstrator with eight transmit and eight receive elements. The demonstrator is built in-house at DTU Space and consists of commercial off-the-shelf components. It features considerable flexibility in terms of waveform generation and data capture, and a collection of measurements with selected of waveforms has been conducted in both indoor and outdoor environments. Based on these measurements, the system behaviour when affected by imperfections is validated, including the presented calibration technique.  <br/