研究目的
To present the first measurement results of a new Orthogonal Frequency Division Multiplexing (OFDM) Multiple Input Multiple Output (MIMO) Radar prototype designed for dynamic multi-user environments with limited RF bandwidth, targeting Urban (Air) Mobility (UAM) applications.
研究成果
The OFDM MIMO radar prototype demonstrates high resolution in azimuth and velocity with a low range resolution, making it suitable for spectrum-efficient obstacle detection in Urban (Air) Mobility applications. Future work will focus on reducing antenna crosstalk and exploring data transfer capabilities.
研究不足
The system has a low range resolution due to the limited bandwidth of 30 MHz. There is also an influence of unwanted antenna crosstalk, and the dynamic range is about 30 dB for a person walking at 55 m.
1:Experimental Design and Method Selection:
The OFDM MIMO radar system was designed with a focus on spectrum efficiency, using a 30 MHz bandwidth for medium-range coverage up to 250 m and a wide field of view in azimuth. The system employs a 2 x 8 MIMO processing for high azimuth resolution and a 20 ms frame-based evaluation for high velocity resolution.
2:Sample Selection and Data Sources:
The measurement involved a dynamic scene with a person walking at a distance of 55 m at a speed of 1.5 m/s, using the radar prototype.
3:5 m/s, using the radar prototype.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: The system consists of a digital board, a Local Oscillator (LO) generator, an RF stage including antennas, and a laptop for control and data transfer. The antennas include sectoral horn antennas for transmission and a uniform linear array of eight 4 x 1 element patch arrays for reception.
4:Experimental Procedures and Operational Workflow:
The radar system was controlled via a gigabit Ethernet interface, with data transferred to the laptop for processing. The OFDM waveforms were generated with a 1024 element Inverse Fast Fourier Transform (IFFT), and the received signals were processed to extract range, velocity, and azimuth information.
5:Data Analysis Methods:
The data was analyzed using FFT and IFFT techniques to reconstruct azimuth and velocity information, respectively, from the received signals.
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