In this paper the permutation entropy (PE) obtained from heart rate variability (HRV) is analyzed in a statistical model. In this model we also integrate other feature extraction techniques, the cepstrum coefficients derived from the same HRV and a set of band powers obtained from the electrocardiogram derived respiratory (EDR) signal. The aim of the model is detecting obstructive sleep apnea (OSA) events. For this purpose, we apply two statistical classification methods: Logistic Regression (LR) and Quadratic Discriminant Analysis (QDA). For testing the models we use seventy ECG recordings from the Physionet database which are divided into equal-size learning and testing sets. Both sets consist of 35 recordings, each containing a single ECG signal. In our experiments we have found that the features extracted from the EDR signal present a sensitivity of 65.6% and specificity of 87.7% (auc = 85) in the LR classifier, and sensitivity of 59.4% and specificity of 90.3% (auc = 83.9) in the QDA classifier. The HRV-based cepstrum coefficients present a sensitivity of 63.8% and specificity of 89.2% (auc = 86) in the LR classifier, and sensitivity of 67.2% and specificity of 86.8% (auc = 86.9) in the QDA. Subsequent tests show that the contribution of the permutation entropy increases the performance of the classifiers, implying that the complexity of RR interval time series play an important role in the breathing pauses detection. Particularly, when all features are jointly used, the quantification task reaches a sensitivity of 71.9% and specificity of 92.1% (auc = 90.3) for LR. Similarly, for QDA the sensitivity is 75.1% and the specificity is 90.5% (auc = 91.7).

This article presents a radio frequency system that can be used to perform precise vertical landings of drones. The system is based on the three-way phase shift detection of a signal transmitted from the landing point. The antenna system is designed by taking into account parameters such as landing tracking area, analog-to-digital converter (ADC) resolution, phase detector output range, antenna polarization, and the effect of antenna axial ratio. The fabricated prototype consists of a landing point antenna that transmits a signal at 2.46 GHz, as well as a drone triantenna system that includes a phase shift detection circuitry, ADC, and a simple control program that provides the correction instructions for landing. The prototype provides an averaged output data rate (ODR) suitable for landing maneuvers (>300 Hz). A simple system calibration procedure (detector output zeroing) is performed by aligning the antenna system. The measurements performed at different altitudes demonstrate both the correct operation of the proposed solution and its viability as an instrument for precision vertical landings.

This article presents a circuit for the precise vertical landing of drones based on a three phase-shifts detection of a single frequency transmitted from the landing point. The circuit can be considered as a new navigation sensor that assists in guidance corrections for landing at a specific point. The circuit has three inputs to which the signal transmitted from an oscillator located at the landing point arrives with different delays. The input signals are combined in pairs in each of the three analog phase detectors, after having passed through 3 dB at 90° hybrid couplers that guarantee a theoretical nonambiguous phase shift range of ±90°. Each output has a voltage that is proportional to the phase shift between each of the input signals, which in turn depends on the position relative to the landing point. A simple landing algorithm based on phase shift values is proposed, which could be integrated into the same flight control platform, thus avoiding the need to add additional processing components. To demonstrate the feasibility of the proposed design, a triangular phase shift detector prototype has been implemented using commercial devices. Calibration and measurements at 2.46 GHz show a dynamic range of 30 dB and a nonambiguous detection range of ±80° in the worst cases. Those specs let us track the drone during the landing maneuver in an inverted cone formed by a surface with a ±4.19 m radius at 10 m high and the landing point.

This paper presents a new procedure for phase detector measurements that allows the use of generators that share a 10 MHz reference oscillator but do not synchronize in phase, in other words, quasi-synchronized RF generators. The objectives are taking advantage of the benefits of using two generators but recovering lower-cost generators that have worse synchronization performance and opening the door to the possibility of using a very simple control element based in Arduino Uno and cheaper instruments. The new procedure is characterized by continuously alternating calibration and measurement sequences to make up for the phase drift of quasi-synchronized generators and guarantee a maximum phase error specification (±1° in this paper). Data acquisition has been divided in two stages: measurement of detector curves without phase reference (in-phase and phase-shifted) and measurement of reference data. All the data is later combined to obtain correctly referenced in-phase detector curves. The technique can be reproduced with other equivalent instrumentation. The novel procedure that allows compensation for errors (amplitude, phase shift, mismatching, etc.) is detailed, and its relation to the required measurement accuracy is amply discussed. The proposed technique is applied to characterize a phase detector based on in-phase and phase-shifted multiplication from 3 to 8 GHz with 1 GHz step. Measurements have a final maximum error of ±2° for both frequency and calibrated input power, according to the accuracy specifications of the VNA used to calibrate the signal distribution network, added to the ±1° specified in this new procedure.