Quantum devices have the potential to revolutionize applications in computing, communications, and sensing; however, current state-of-art resources must operate at extremely low temperatures, making the routing of microwave control and readout signals challenging to scale. Interest in microwave photonic solutions to this problem has grown in recent years, in which control signals are delivered to the cold stage via optical fiber, where they are converted to electrical signals through photodetection. Overall link performance depends strongly on the characteristics of the photodiode, yet detailed measurements of many detector properties remain lacking at cold temperatures. In this work, we examine and compare the performance of a modified uni-traveling carrier photodiode (MUTC-PD) at both room (300 K) and liquid nitrogen (80 K) temperatures, focusing in particular on responsivity, bandwidth, and linearity. In line with previous work, we find a sharp reduction in responsivity at 1550 nm as temperature decreases, while RF bandwidth remains steady. Interestingly, our linearity tests reveal that the RF output saturates more quickly at 80 K, suggesting reduced linearity with lower temperature, the cause of which is still under investigation. Our results should help contribute to the understanding and future design of highly linear cryogenic quantum links.
KEYWORDS: Radar, Antennas, Compressed sensing, Data fusion, Data centers, Detection theory, Target detection, Chemical elements, Phased arrays, Signal to noise ratio
Compressive sensing (CS) based multi-input multi-output (MIMO) radar systems that explore the sparsity
of targets in the target space enable either the same localization performance as traditional methods but
with significantly fewer measurements, or significantly improved performance with the same number of
measurements. However, the enabling assumption, i.e., the target sparsity, diminishes in the presence of
clutter, since clutters is highly correlated with the desire target echoes. This paper proposes an approach to
suppress clutter in the context of CS MIMO radars. Assuming that the clutter covariance is known, Capon
beamforming is applied at the fusion center on compressively obtained data, which are forwarded by the
receive antennas. Subsequently, the target is estimated using CS theory, by exploiting the sparsity of the
beamformed signals.
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