Review Reports
- Miao Wu1,
- Xianzhou Jin1 and
- Xin Qi2
- et al.
Reviewer 1: Anonymous Reviewer 2: Anonymous Reviewer 3: Chen Wu
Round 1
Reviewer 1 Report (Previous Reviewer 3)
Comments and Suggestions for AuthorsDear Authors,
See the attached pdf file.
Best Regards,
Reviewer
Comments for author File: 
Comments.pdf
Author Response
Comments 1: [The introduction must clearly emphasize the scientific contributions of your paper. This is common practice in writing scientific papers. I don't see that it exists in the paper at all, and that's the most important thing. You solve the problem in an original way, so emphasize exactly what the scientific contribution is.]
Response 1: Thank you for pointing this out. We agree with this comment.
[This method significantly improves the accuracy of zero-point phase tracking for the eLoran signal, and enhances tracking precision for three-period zero-crossing. It maintains the measurement reference deviation of the measurement pulse within a narrow range. In addition to suppressing zero drift, the method also reduces waveform distortion, thereby improving period discrimination accuracy and further decreasing positional line deviation resulting from phase misalignment.]
Comments 2: [According to the journal's rules, there must be an option to click on Section 2, Section 3, etc. So, corrections start from line 86.]
Response 2: Thank you for highlighting this important aspect. We have revised this to emphasize this point.
[It has been carefully revised in the original manuscript.]
Comments 3: [Your Answer 7 is particularly interesting. The thresholding problem is also present in other areas and systems, such as HFSWRs, where performance depends heavily on this choice. Go to Google browser and type keywords: “RD-HR map threshold determination”. See the following articles, which are of a more recent date, where the threshold determination in HFSWRs is described to obtain RD maps and perform detection from them (geometrically and experimentally-based methods). Perhaps it would be good to mention 1-2 references related to this research topic. In my opinion it can be very useful, because you definitely can improve detection threshold procedure in another way. This could be one of the ideas.]
Response 3: Thank you for pointing this out. We agree with this comment.
[The selection of the threshold significantly influences the performance of simulation experiments, particularly in high-frequency surface wave radars (HFSWRs), where this choice is critical. The threshold simulation experiments presented in this paper draw inspiration from the threshold determination process used in HFSWRs. This de-termination relies on both geometric and experimental methods, and the resulting RD graph will facilitate detection [24,25].]
Revised manuscript:
- Golubović, D.; Marjanović, D. An Experimentally-Based Method For Detection Threshold Determination in HFSWR’s High-Resolution Range-Doppler Map Target Detection. In 2025 24th International Symposium INFOTEH-JAHORINA (INFOTEH); 2025; pp 1–6.https://doi.org/10.1109/INFOTEH64129.2025.10959225.
- Golubović, D.; Insiue; Begrde; Serbi; Golubović, D. The Future of Maritime Target Detection Using HFSWRs: High-Resolution Approach[C]//2024 32nd Telecommunications Forum. 2024:1-8. https://d.wanfangdata.com.cn/Conference/811a15500fcd8154d010b791bde18ef0.
Comments 4: [You use Gaussian window. It would be good if you just commented on why you chose this particular window and how it would possibly affect it if you took another one.]
Response 4: Thank you for pointing this out. We agree with this comment.
[When applying the NTFT to a finite-length time series, the window function becomes incomplete for a specific duration at both the beginning and the end of the dataset. This incompleteness results in the unavailability of NTFT coefficients at the edges, leading to inaccuracies in the signal reconstruction at these locations. This phenomenon represents an unavoidable edge effect associated with signal reconstruction using inaction methods. Consequently, it is essential to account for the range influenced by the edge effect when conducting standard time-frequency transformations. Furthermore, the extent of the edge effect is contingent upon the window width of the summation window function. Therefore, this study employs the standard Gaussian window, which approaches zero at an infinite boundary.]
Comments 5: [Explain the signals defined in this way, which are described by equations (39) and (40). This should be clear to the readers. Or, if necessary, provide a reference from where these equations were taken.]
Response 5: Thank you for pointing this out. We agree with this comment.
[ The equations (39) and (40) are defined in accordance with Reference 31.]
Comments 6: [It is not a good solution to have the caption of the figure separately on the next page. In your case, it is figure 7. Try to correct this. In such reputable journals as this one, this is not allowed. The same applies to Figure 10.]
Response 6: Thank you for highlighting this important aspect. We have revised this to emphasize this point.
[It has been carefully revised in the original manuscript.]
Comments 7: [“The Figure 6 simulation results indicate” → “The Figure 6 indicate”. Check the entire text and correct errors of this type.]
Response 7: Thank you for highlighting this important aspect.
["The Figure 6 simulation results indicate " has been changed to " The Figure 6 indicate "，The rest of the parts have also been revised.]
Comments 8: [You use the first 400 μs eLoran single pulse signals to estimate the performance. Explain to readers why you are taking such a sample size and how its length may affect the results obtained.]
Response 8: Thank you for pointing this out. We have revised this to emphasize this point.
[During the initial 350 of the eLoran signal, the signal amplitude approaches zero. This paper selects the first 400 for simulation and experimentation to compare the edge effects of the four joint algorithms following signal reconstruction.]
Comments 9: [What does the term " relatively high SNR" refer to? There may be some confusion here, so we need to define this precisely, let's say you add what values you mean.]
Response 9: Thank you for pointing this out. We agree with this comment.
[The signals intercepted from coastal ports exhibit significant interference due to environmental obstructions, resulting in a SNR below -10dB. Analysis of the single-pulse waveform reveals noticeable distortion, which can lead to errors in period discrimination. To facilitate signal analysis, amplitude compensation was applied to the front-end digital signals collected from coastal ports. In contrast, the signals intercepted in inland cities demonstrate a high SNR exceeding 10dB.]
Author Response File: Author Response.pdf
Reviewer 2 Report (Previous Reviewer 2)
Comments and Suggestions for AuthorsThe manuscript looks much better now and is recommended for publication after a minor revision. There are two minor issues for the authors' attention:
1) Avoid excessive paragraph breaks for Equations. For example, sentences starting with "where" when describing parameters in the equations should be in the same paragraph as the equation being described, with no indentation spaces. Up to Equation 34, there are too many paragraph breaks, which may easily confuse readers in terms of textual logic.
2) Please provide the calculation formula for the Signal-to-Noise Ratio (SNR). Regarding the particularity of 25 μs in Equation 16, why is 25 microseconds chosen? Is it the signal duration? Is 25 μs adopted for all other waveforms? From Figure 3, it seems that 25 microseconds is not the part where the signal is the strongest. This still makes the SNR definition be confusing.
Author Response
Comments 1: [Avoid excessive paragraph breaks for Equations. For example, sentences starting with "where" when describing parameters in the equations should be in the same paragraph as the equation being described, with no indentation spaces. Up to Equation 34, there are too many paragraph breaks, which may easily confuse readers in terms of textual logic.]
Response 1: Thank you for pointing this out. We agree with this comment.
[It has been carefully revised in the original manuscript.]
Comments 2: [Please provide the calculation formula for the Signal-to-Noise Ratio (SNR). Regarding the particularity of 25 μs in Equation 16, why is 25 microseconds chosen? Is it the signal duration? Is 25 μs adopted for all other waveforms? From Figure 3, it seems that 25 microseconds is not the part where the signal is the strongest. This still makes the SNR definition be confusing.]
Response 2: Thank you for your thoughtful review and careful assessment of our manuscript. We have revised this to emphasize this point.
[The 25 were selected according to the definition of signal level outlined in the General Technical Conditions for Marine Loran-C Receiving Equipment (Reference 31). The SNR established for the subsequent waveforms were all determined based on this definition]
Author Response File: Author Response.pdf
Reviewer 3 Report (Previous Reviewer 1)
Comments and Suggestions for Authorsgreatly improved, comments see attached.
Comments for author File: Comments.pdf
Author Response
Comments 1: [how to define zero-point drift percentage?]
Response 1: Thank you for pointing this out. We agree with this comment.
[Zero-point drift refers to the deviation observed in the time series between the positive zero-crossing point of the third period of the reconstructed signal and that of the original signal.]
Comments 2: [what is antenna bottom current?]
Response 2: Thank you for pointing this out. We agree with this comment.
[The bottom current of the antenna denotes the peak current that flows from the output terminal of the transmitter into the ground network at the base of the antenna tower within the eLoran transmission system. This current directly influences the field strength and coverage area of the radiated signal. In the time domain, the current at the base of the antenna appears as a 100 kHz radio frequency pulse current, modulated in accordance with the shape of the eLoran envelope.]
Comments 3: [why 65? and why tao<t<tao-65?]
Response 3: Thank you for your thoughtful review and careful assessment of our manuscript. We have revised this to emphasize this point.
[The eLoran signal attains its maximum rising speed at 65, thus the time (t) for the eLoran pulse phase ranging difference system is established at 65 as the threshold. A detailed derivation is available in the literature: Wu, M., Zhu, Y., Li, F., Xu, J. Radio Navigation Principle and Signal Receiving Technology; National Defense Industry Press: Beijing, China, 2015; ISBN 978-7-18-09795-5. (Reference 4)]
Comments 4: [what is the imaginary line?]
Response 4: Thank you for pointing this out. We agree with this comment.
[The imaginary line is the envelope of the eLoran signal.]
Comments 5: [how do you get this NTFT plot?]
Response 5: Thank you for your thoughtful review and careful assessment of our manuscript. We have revised this to emphasize this point.
[The NTFT spectrum is obtained through standard time-frequency transformation. The correlation coefficient, as defined in Equation 19, is then extracted and represented in a pcolor diagram. In this diagram, the horizontal axis denotes time (in ), the vertical axis represents frequency (in kHz), and the color intensity indicates the energy level corresponding to each time-frequency position, and the dashed line represents the maximum value of the eLoran signal spectrum over time.]
Comments 6: [how to get this plot from (1)? or what relation between them?]
Response 6: Thank you for raising this out. We agree with this comment.
[Figure 1 (a) illustrates the time-domain representation of the eLoran signal, which was directly simulated and generated in MATLAB using Equation 1. Figure 1 (b) denotes the frequency-domain characteristics of the eLoran signal. The vertical axis denotes that the frequency range of the eLoran signal is concentrated between 90 kHz and 110 kHz, while the color depth indicates the energy magnitude at the corresponding time and frequency.]
Comments 7: how this is shown in figure (1)a?]
Response 7: Thank you for your thoughtful review and careful assessment of our manuscript. We have revised this to emphasize this point.
[It has been carefully revised in the original manuscript.]
Comments 8: [please add more detail words on how to read the Figure 2, linked with above equations.]
Response 8: Thank you for pointing this out. We agree with this comment.
[The input signal is first constructed using MATLAB. Subsequently, the frequency domain range of 90-110 kHz is established based on the NTFT spectrum diagram (Equation 19). This main frequency band of 20 kHz is finely divided into 200 sub-frequency bands. The energy proportion of each sub-frequency band within the main frequency band is then calculated. The signal for each sub-frequency band is re-constructed using a non-action algorithm (Equations 25-36). Finally, weighted fusion is performed according to the energy proportions of the sub-frequency bands, resulting in the superimposition and reconstruction of the original signal.]
Comments 9: [what of these frequency bandwidths? Multi-narrowband frequency?]
Response 9: Thank you for pointing this out. We agree with this comment.
[The frequency bandwidth of eLoran is defined as 20 kHz (90-110 kHz). Multi-band narrowband interference involves the superposition of narrowband interference from multiple distinct frequencies, where these frequencies correspond to the values of the added narrowband interference. Narrowband interference (NBI) is a prevalent form of interference encountered in eLoran receivers, primarily characterized by sinusoidal interference signals that possess significantly greater energy than the eLoran signal.]
Comments 10: [what means noise frequency? why pick these frequencies?]
Response 10: Thank you for your thoughtful review and careful assessment of our manuscript. We have revised this to emphasize this point.
[Narrow Band Interference (NBI) is a prevalent form of interference encountered in eLoran receivers. It primarily consists of sinusoidal interference signals that possess significantly greater energy than the eLoran signal, thereby severely affecting the positioning accuracy of these receivers. Based on the frequency relationships between narrowband signals and eLoran systems, NBI can be categorized into synchronous interference, near-synchronous interference, and asynchronous interference. Synchronous interference occurs when the spectral line of the interference signal aligns with the Roland C spectral line, indicating that the frequency of the interference signal is an integer multiple of the minimum group repetition interval of the eLoran signal. Near-synchronous interference is characterized by interference signals whose frequency spectral lines are relatively close to the eLoran spectral lines, falling within the tracking bandwidth of the receiver. Its effects are akin to those of synchronous interference. In contrast, asynchronous interference arises when the frequency spectral lines of narrowband interference are distanced from the eLoran spectral lines, with the frequency difference exceeding the tracking bandwidth.]
Comments 11: [any reasons of pick these waveforms? can you discuss how this setting is close to real scenarios?]
Response 11: Thank you for pointing this out. We agree with this comment.
[Band-limited random noise and narrowband interference are prevalent types of interference encountered in eLoran receivers, consistent with natural scenarios. The source of this interference can be traced to the General Technical Conditions for Marine Loran-C Receiving Equipment (Reference 31).]
Comments 12: [All of your wave plots are shown as normalized outputs. Can you clarify what they are normalized to? I suggest instead defining a similarity function between the filtered signal and the standard signal, specifically in the region in the block. Since the main concern is the correctness of the zero‑crossings, the similarity measure should emphasize that aspect. Whether other parts of the waveform match or not is less important.]
Response 12: Thank you for pointing this out. We agree with this comment.
[Normalization is essential for assessing the matching degree of the waveform. This is due to the fact that, in addition to ensuring the accuracy of the zero-crossing point in the third period, the waveform's matching degree also indirectly influences the positioning accuracy of the eLoran receiver. The identification of the zero-crossing point in the third period typically relies on the waveform characteristics of the Roland C signal for discrimination. Distortion of the waveform can result in errors during period discrimination, leading to phase tracking misalignment. Such misalignment can correspond to a positional deviation of up to 3 kilometers.]
Comments 13: [this is too long. suggest add a "discussion" section, and make conclusion on your contribution.]
Response 13: Thank you for pointing this out. We agree with this comment.
[It has been carefully revised in the original manuscript.]
Author Response File: Author Response.pdf
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe paper is being rejected because it is not adequately written for publication. Although the content may be of interest to general readers, the manuscript requires substantial revision to meet the minimum standards expected for a journal article. Please ensure that your writing is clear, well-structured, and professionally presented. Additionally, do not assume that readers possess the same level of background knowledge as you—provide sufficient context and explanation to make your work accessible.
Comments for author File: Comments.pdf
please carefully revise the paper, and submit again!
Author Response
Please refer to the attachment.
Author Response File: Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsThis paper focuses on practical application challenges of the eLoran system and proposes a segmented inaction combined adaptive algorithm for suppressing zero-point drift in eLoran signals, while also effectively mitigating waveform distortion. The research on the proposed method is systematic and comprehensive, and the simulation and experimental data are generally reliable. Overall, I believe this work is suitable for publication in the Electronics journal. However, to further enhance the quality of the manuscript prior to formal acceptance, I kindly suggest the authors address the following points for improvement:
1. Use of Abbreviations
(1) I would recommend ensuring strict consistency between abbreviations and their full forms. For instance, there appears to be a potential mismatch between the abbreviations RMSE (line 19) and R-RMSE (line 20) and their corresponding full expressions.
(2) I suggest avoiding abbreviations in the keyword list (e.g., VSS-LMS in line 24) to improve clarity for readers.
A thorough full-text check would be beneficial to refine the use of abbreviations throughout the manuscript.
2. English Expression
(1) I note that the English writing of the manuscript has room for further polishing. I advise the authors to carefully review and refine the grammatical structures and word choices to make the expression more natural, avoiding potential Chinglish phrasing.
(2) Additionally, a detailed proofread of the entire text would help eliminate spelling inconsistencies. For example, "the China Academy of Sciences" (line 60) should be adjusted to "the Chinese Academy of Sciences".
3. Introduction
(1) I think it would be helpful to elaborate slightly on the core problems addressed in this work (zero-point drift and waveform distortion), including their underlying causes, practical significance (i.e., potential impacts on eLoran system performance), and the key challenges associated with their mitigation.
(2) For the existing work mentioned in lines 59-60, I recommend adding relevant references to strengthen the contextualization of the research.
4. Main Text
(1) Standardizing the formatting of formulas and symbols would greatly improve readability. As a general academic convention, variables are presented in italics, constants in roman font, and vectors/matrices in bold italic—I observe some inconsistent use of italic and roman fonts in the current manuscript that could be adjusted.
(2) Section 2.3 contains relatively extensive background introduction and literature review. I suggest condensing this content and integrating it into the Introduction, which would allow the main text to focus more directly on the core research. This revision could be coordinated with the suggestions in Comment 3.
(3) Regarding Figure 4: With only 4 sampling points provided, I feel the evidence supporting the optimality of a window length of 100 might be further reinforced. For example, could smaller offset values exist within the window length range of 100–120? I recommend increasing the number of sampling points to verify this conclusion. Since the optimal range is already indicated in line 247, conducting more detailed investigations with additional sampling points within this range would be valuable.
(4) For formula presentation, I suggest reducing the segmentation of Formulas (7)–(21). Explanations of parameters belonging to the same formula should be included in a single paragraph for better coherence.
(5) Adding a schematic diagram (e.g., an enlarged local waveform image) to illustrate the zero-point drift phenomenon would enhance clarity. Given the small magnitude of zero-point drift, the current waveform displays make it difficult to intuitively observe the relevant results.
(6) In the experimental section, I advise providing specific information about the signal-to-noise ratio (SNR) of the actual signals, along with the corresponding SNR definition adopted—this would improve the reproducibility of the work.
(7) The Introduction mentions that the proposed method exhibits excellent performance under strong interference and low SNR conditions (lines 64–65). I believe supplementing appropriate simulation or experimental results to support this claim would strengthen the manuscript. It would be helpful to clarify the specific thresholds of interference intensity and SNR within which the proposed method maintains effectiveness, particularly in scenarios where existing methods may struggle.
Author Response
Please refer to the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsDear Authors,
See the attached pdf file.
Best Regards,
Reviewer
Comments for author File: Comments.pdf
There are many expressions that can be simplified.
Author Response
Please refer to the attachment.
Author Response File: Author Response.pdf