the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 02 Sep 2026
Development of a UAV-based fully-airborne transient electromagnetic system
Abstract. In order to meet the challenges of transient electromagnetic exploration in complex terrain, a lightweight, low-noise, three-component, fully-airborne transient electromagnetic system is designed based on an unmanned aerial vehicle platform. By receiving the three-component electromagnetic field, reliable detection of the normal component even in undulating terrain is enabled, while also offering a theoretical basis for correcting errors arising from receiver coil oscillation. Through a system-level optimization design, the system balances weight and transmission power, resulting in a lightweight (14.94 kg), large transmitting magnetic moment (2250 Am²), and extremely low system noise (1.7 nT/s) configuration. A series of performance verification experiments and field tests verify the stability and practical operability of the proposed system in field applications. Comparisons between the inversion results of the collected detection data and borehole logging data further confirm the reliability of the system. Therefore, this system can provide an effective technical approach and solid data support for the fine detection of subsurface interfaces within a depth of 50 meters.
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Status: final response (author comments only)
- RC1: 'Comment on egusphere-2026-4378', Shengquan Zhang, 06 Sep 2026
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RC2: 'Comment on egusphere-2026-4378', Anonymous Referee #2, 12 Sep 2026
This paper presents a fully-airborne transient electromagnetic detection system based on an UAV. It focuses on the hardware system design, integration and practical application performance. The content and overall quality of the manuscript meet the journal’s requirements. However, several points still need to be revised or clarified,
1. The abstract presents complete research logic and sufficient quantitative technical parameters, but the research novelty and technical improvements over conventional airborne TEM systems are not explicitly highlighted. In particular, the comparison with current technics.
2. Section 2.1 uses a lot long compound sentences, which could be difficult to follow for readers. A simplified description is necessary.
3. Line.105: The design of high-precision synchronous clock is used to provide time matching between transmitter and receiver, and it could also be noticed from Fig.1 that there is a synchronization cable between transmitter and receiver, therefore what is that used for?
4. How is the lightweight towed bird design realized in section 2.4? Is it achieved by lightweight materials, structural optimization, or other measures?
5. Are the inversion results presented in Fig. 10 derived from threecomponent data?
Citation: https://doi.org/10.5194/egusphere-2026-4378-RC2 -
RC3: 'Comment on egusphere-2026-4378', Anonymous Referee #3, 22 Sep 2026
The manuscript ” Development of a UAV-based fully-airborne transient electromagnetic system” by Guo et al. is an interesting read and well suited for the Geoscientific Instrumentation journal. The manuscript is generally easy to follow and the language is ok, but the manuscript would benefit from a proofreading by an expert in scientific English. I understand the difficulties in presenting a scientific instrument while at the same time keeping some tricks-of-the-trade confidential. However, since the authors opted to publish it in a scientific journal, more details and accuracy in the presentation should be added to the manuscript, so the research becomes reproducible.
My recommendation is that the manuscript should undergo a major revision before it can be accepted. See below for detailed comments
Line 26: remove “developed by Hydro Geophysics”. There is no such company.
Line 30: fields --> field
Line 40: filed --> field
Line 65: Please explain the dual clamping in more detail. It might be beneficial to add a figure with a block diagram or timing diagram.
Line 79: The stability of the transmitter cannot be judged from figure 2. It would be appropriate with some statistical measures, e.g., the peak current is 20.0±0.5 A or similar.
Figure 2: This appears to be a screenshot from a digital oscilloscope. It is somewhat pixelated and the time axis cannot be seen directly but must be inferred. I suggest that the author load the data into, e.g., MATLAB, and make a proper figure.
Line 86: Is “Research” really the right word here. From the manuscript content “development” seems more appropriate.
Line 87: The authors are not very clear on the actual sensor. Does it measure magnetic field or does it measure the derivative of the magnetic field by measuring the voltage across an induction coil?
Line 88-89: I don’t see any circuit design in Figure 3.
Figure 3: Not all readers will easily understand all the abbreviations. Please explain PL, PS, OCXO in the caption or in the text. What is the meaning of “1” in Hx1?
Line 103: Date --> Data
Line 106: It is not obvious how “the noise level of the receiver” was tested. Is it possible that it is only the noise level of a short-circuited amplifier that is tested? Please add details.
Line 107: Why is the noise level for X and Z quoted with three significant digits while only two are used for Y?
Figure 4: This figure should be revised. It is bad practice to use unequal scaling across the three figures. I suggest that the three data sets are plotted on one graph instead. This will make similarities and differences among channels immediately appear.
Line 120: It is not clear to me what definition of bandwidth is used here. If nothing else is quoted I would assume a 3 dB bandwidth. However, the signal drops by two orders of magnitude across the plot in figure 5B. Please revise.
Line 124: The authors mention a compensation coil, but it is not discussed. I assume the compensation coil is just what is normally referred to as a bucking coil. Please add details on this issue.
Line 145: An important feature of a UAV system is the actual flight time, but this number is missing in the manuscript.
Figure 7: The figure shows a 10 m distance between drone and payload. How was this distance decided. What is the level of noise in the data caused by interference from the drone?
Figure 8: I suggest that the figure is augmented with a couple of standard sounding examples, i.e. a log-log plot of dB/dt signal versus time following a single pulse. This would make it easier for the reader to assess the data quality.
Figure 9: Please indicate the size of the survey on the map by adding a ruler. What is the cause of the somewhat large deviations from the intended flight path?
Line 200, Table 2: Data are here quoted with a precision of 1 cm. This number is clearly completely out of context given, e.g., the footprint of the EM field at 30 m depth. If you insist on this precision, please explain how it comes about.
Line 221, Discussion. An important problem in airborne measurements is motion-induced noise, which can be significant for TEM, where movements of the receiver coil in the earth magnetic field can give dB/dt variations much larger than the TEM signal. However, this issue is not discussed in the manuscript. It would be appropriate to add this. A figure with flight data from a measurement done without turning on the transmitter could provide insight.
Line 221, Discussion. This section is not particularly insightful. Line 225-232 belongs in the introduction to the manuscript and line 236-243 is a conclusion, not a discussion.
Line 234. The use of “pioneered” is overselling. E.g., the authors refer in Table 1 to three existing systems.
Citation: https://doi.org/10.5194/egusphere-2026-4378-RC3
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Focusing on the demand for high-efficiency exploration in complex terrains, this paper breaks through the limitations of the semi-airborne "ground-transmitted and air-received" mode and achieves fully-airborne TEM detection with an "air-transmitted and air-received" architecture. The lightweight design of the system is adaptable to small and medium-payload UAVs, lowering deployment barriers and operational costs, and is suitable for rapid reconnaissance in inaccessible areas such as mountainous regions and landslide-prone areas.
In terms of system design, the system accommodates both deep and shallow detection requirements while reducing average power consumption, effectively resolving the trade-off between UAV payload limits and detection performance. The developed three-component low-noise sensor expands data dimensionality compared with analogous single-component systems, providing a data foundation for attitude correction and fine-scale interpretation of geological bodies. Furthermore, a three-component correction model constructed with IMU attitude data effectively mitigates the impact of flight attitude fluctuations on measurement results.
For system validation, multi-level verifications are carried out sequentially from module-level performance testing to system-level field trials. The conclusions are well supported by experimental data, demonstrating clear engineering application value.
Problems and Revision Suggestions