Rydberg atoms have been used for measuring radio-frequency (RF) electric (E)-fields due to their strong dipole moments over the frequency range of 500 MHz-1 THz. For this, electromagnetically induced transparency (EIT) within the Autler-Townes (AT) regime is used such that the detected E-field is proportional to AT splitting. However, for weak E-fields AT peak separation becomes unresolvable thus limiting the minimum detectable E-field. Here, we demonstrate using the Rydberg atoms as an RF mixer for weak E-field detection well below the AT regime with frequency discrimination better than 1 Hz resolution. A heterodyne detection scenario with two E-fields incident on a vapor cell filled with cesium atoms is used. One E-field at 19.626000 GHz drives the 34D5/2 → 35P3/2 Rydberg transition and acts as a local oscillator (LO) and a second signal E-field (Sig) of interest is at 19.626090 GHz. In the presence of the LO, the Rydberg atoms naturally down convert the Sig field to a 90 kHz intermediate frequency (IF) signal. This IF signal manifests as an oscillation in the probe laser intensity through the Rydberg vapor and is easily detected with a photodiode and lock-in amplifier. In the configuration used here, E-field strength down to ≈ 46 μV/m ± 2 μV/m were detected with a sensitivity of ≈ 79 μVm−1Hz−1/2. Furthermore, neighboring fields 0.1 Hz away and equal in strength to Sig could be discriminated without any leakage into the lock-in signal. For signals 1 Hz away and as high as +60 dB above Sig, leakage into the lock-in signal could be kept below -3 dB.

The recent developments of Rydberg atom-based sensors with the ability to measure phase have made it possible to receive digital phase-modulated signals. In this letter, we demonstrate the reception of binary phase-shift keying, quadrature phase-shift keying, and quadrature amplitude modulation signals with an atom-based receiver. We present measured values of error vector magnitude as a function of symbol rate for various modulation schemes and discuss the bandwidth of a Rydberg atom-based receiver system. The results show that we can now interrogate ensembles of atoms to such extent that we can use them to receive data from a phase-modulated communication signal.

Three-dimensional (3-D) printing is finding applications across many areas and may be a useful technology for antenna fabrication for cube satellites (CubeSats). However, the quality of an antenna produced using 3-D printing must be considered if this technology can be relied upon. We present gain and far-field pattern results for the feed horn of the radiometer payload of the CubeSat PolarCube. The corrugated feed horn is constructed from AlSi10Mg alloy and fabricated using powder bead fusion (PBF). Measurements were performed at the atmospheric oxygen line of 118.7503 GHz with the National Institute of Standards and Technology (NIST) Configurable Robotic Millimeter-Wave Antenna (CROMMA) facility in Boulder, Colorado. A comparison of these measurements to theoretical predictions provides an assessment of the performance of the feed horn.

Deep subwavelength radio-frequency (RF) imaging with atomic Rydberg sensors has overcome fundamental limitations of traditional antennas and enabled ultra-wideband detection of omni-directional time varying fields all in a compact form factor. However, in most applications, Rydberg sensors require the use of a secondary strong RF reference field to serve as a phase reference. Here, we demonstrate a new type of Rydberg sensor for angle-of-arrival (AoA) sensing, which utilizes subwavelength imaging of standing wave fields. By placing a metallic plate within the Rydberg cell, we can determine the AoA independent of the strength of incoming RF field and without requiring a secondary strong RF phase reference field. We perform precision AoA measurements with a robotic antenna positioning system for 4.2, 5.0, and 5.7 GHz signals and demonstrate a 1.7° polar angular resolution from 0° to 60° AoA and 4.1° over all possible angles.

In this work, we present methods allowing parallel, hybrid, and serial manipulators to be analyzed, calibrated, and controlled with the same analytical tools. We introduce a general approach to describe any robotic manipulator using established serial-link representations. We use this framework to generate analytical kinematic and calibration Jacobians for general manipulator constructions using null space constraints and extend the methods to hybrid manipulator types with complex geometry. We leverage the analytical Jacobians to develop detailed expressions for post-calibration pose uncertainties that are applied to describe the relationship between data set size and post-calibration uncertainty. We demonstrate the calibration of a hybrid manipulator assembled from high precision calibrated industrial components resulting in 91.1 $\mathsf{\mu }$m RMS position error and 71.2 $\mathsf{\mu }$rad RMS rotation error, representing a 46.7% reduction compared to the baseline calibration of assembly offsets.

We propose compressive sensing approaches for broadband spherical near-field measurements that reduce measurement demands beyond what is achievable using conventional single-frequency compressive sensing. Our approaches use two different compressive signal models-sparsity-based and low-rank-based-whose viability we establish using a simulated standard gain horn antenna. Under mild assumptions on the device being tested, we prove that sparsity-based broadband compressive sensing provides significant measurement number reductions over single-frequency compressive sensing. We find that our proposed low-rank model also provides an effective means of achieving broadband compressive sensing, using numerical experiments, with performance on par with the best broadband sparsity-based method. Exemplifying these best-case results, even in the presence of measurement noise, the methods we propose can achieve relative errors of -40 dB using about 1/4 of the measurements required for conventional sampling. This is equivalent to about 1/2 sample per unknown, whereas traditional spherical near-field measurements require a minimum of roughly 2 measurements per unknown.