Non-intrusive soil carbon content quantification methods using machine learning algorithms:A comparison of microwave and millimeter wave radar sensors

Agricultural and forestry biomass can be converted to biochar through pyrolysis gasification,making it a significant carbon source for soil.Applying biochar to soil is a carbon-negative process that helps combat climate change,sustain soil biodiversity,and regulate water cycling.However,quantifying soil carbon content conventionally is time-consuming,labor-intensive,imprecise,and expensive,making it difficult to accurately measure in-field soil carbon’s effect on storage water and nutrients.To address this challenge,this paper for the first time,reports on extensive lab tests demonstrating non-intrusive methods for sensing soil carbon and related smart biochar applications,such as differentiating between biochar types from various biomass feedstock species,monitoring soil moisture,and biochar water retention capacity using portable microwave and millimeter wave sensors,and machine learning.These methods can be scaled up by deploying the sensor in-field on a mobility platform,either ground or aerial.The paper provides details on the materials,methods,machine learning workflow,and results of our investigations.The significance of this work lays the foundation for assessing carbon-negative technology applications,such as soil carbon content accounting.We validated our quantification method using supervised machine learning algorithms by collecting real soil mixed with known biochar contents in the field.The results show that the millimeter wave sensor achieves high sensing accuracy(up to 100%)with proper classifiers selected and outperforms the microwave sensor by approximately 10%–15%accuracy in sensing soil carbon content.

Numerical simulation and inversion of offshore area depth based on x-band microwave radar

A detection method of offshore area depth utilizing the x-band microwave radar is proposed. The method is based on the sea clutter imaging mechanism of microwave radar, and combined with dispersion equation of the liner wave theorem and least square method （LSM）, consequently get the inversion results of water depth in the detected region. The wave monitoring system OSMAR-X exploited by the Ocean State Laborato-ry, Wuhan University, based on a microwave radar has proven to be a powerful tool to monitor ocean waves in time and space. Numerical simulation and inversion of offshore area depth are carried out here; since JONSWAP model can give description of stormy waves in different growth phase, it is suitable for simulation. Besides, some results from measured data detected by OSMAR-X x-band radar located at Longhai of Fujian Province, China, validates this method. The tendency of the average water depths inferred from the radar images is in good agreement with the tide level detected by Xiamen tide station. These promising results suggest the possibility of using OSMAR-X to monitor operationally morphodynamics in coastal zones. This method can be applied to both shore-based and shipborne x-band microwave radar.

Noncontact Monitoring of Relative Changes in Blood Pressure Using Microwave Radar Sensors

This study aims to confirm whether noncontact monitoring of relative changes in blood pressure can be estimated using microwave radar sensors. First, an equation to estimate blood pressure was derived, after which, the effectiveness of the estimation equation was confirmed using data obtained by a noncontact method while inducing variations in blood pressure. We considered that the Bramwell-Hill equation, which contains some parameters that directly indicate changes in blood pressure, would be an appropriate reference to construct an estimation equation for the noncontact method, because measurements using microwave radar sensors can measure minute scale motion on the skin surface induced by the pulsation of blood vessels. In order to estimate relative changes in blood pressure, we considered a simple equation including the pulse transit time (PTT), amplitude of signals and body dimensions as parameters. To verify the effectiveness of the equation for estimating changes in blood pressure, two experiments were conducted: a cycling task using an ergometer, which induces blood pressure fluctuations because of changes in cardiac output, and a task using the Valsalva maneuver, which induces blood pressure fluctuations because of changes in vascular resistance. The results obtained from the two experiments suggested that the proposed equation using microwave radar sensors can accurately estimate relative changes of blood pressure. In particular, relatively favorable results were obtained for the changes in blood pressure induced by the changes in cardiac volume. Although many issues remain, this method could be expected to contribute to the continuous evaluation of cardiac function while reducing the burden on patients.

Assessment of Non-Contact Measurement Using a Microwave Sensor to Jugular Venous Pulse Monitoring

The jugular venous pulse (JVP) waveform provides an insight into right heart function, and its assessment is important in patients with heart failure. However, the conventional pulse-transducer (contact) method for monitoring this waveform is not frequently used because it requires a high degree of skill. The aim of this study was to confirm the effectiveness of a prototype non-contact system that employs microwave radar (24 GHz, 7 mW;non-contact system) for JVP measurement. Experiments were conducted on eight healthy male volunteers (21.88 ± 0.99 years). JVP measurements were compared between the conventional contact method and the proposed non-contact method. Change in JVP waveform was measured in response to an angle of reclining in five steps from the supine position to 75° of elevation. The obtained JVP measurements were similar between the two methods. Because in the non-contact method the faint pulsation of the JVP is not suppressed by the pressure of a sensor placed on the skin, the prototype microwave radar system is particularly suitable for evaluating the JVP waveform.

Broadband photonic ADC for microwave photonics-based radar receiver

A broadband photonic analog-to-digital converter（ADC） for X-band radar applications is proposed and experimentally demonstrated. An X-band signal with arbitrary waveform and a bandwidth up to 2 GHz can be synchronously sampled and processed due to the optical sampling structure. In the experiment, the chirp signal centered at 9 GHz with a bandwidth of 1.6 GHz is sampled and down-converted with a signal-to-noise ratio of 7.20 d B and an improved noise figure. Adopting the photonic ADC in the radar receiver and the above signal as the transmitted radar signal, an X-band inverse synthetic aperture radar system is set up, and the range and cross-range resolutions of 9.4 and 8.3 cm are obtained, respectively.

Ultra-high range resolution demonstration of a photonics-based microwave radar using a high-repetition-rate mode-locked fiber laser

We experimentally demonstrate the ultra-high range resolution of a photonics-based microwave radar using a high repetition rate actively mode-locked laser（AMLL）. The transmitted signal and sampling clock in the radar originate from the same AMLL to achieve a large instantaneous bandwidth. A Ka band linearly frequency modulated signal with a bandwidth up to 8 GHz is successfully generated and processed with the electro-optical upconversion and direct photonic sampling. The minor lobe suppression（MLS） algorithm is adopted to enhance the dynamic range at a cost of the range resolution. Two-target discrimination with the MLS algorithm proves the range resolution reaches 2.8 cm. The AMLL-based microwave-photonics radar shows promising applications in high-resolution imaging radars having the features of high-frequency band and large bandwidth.