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arxiv: 2603.04813 · v3 · submitted 2026-03-05 · 📡 eess.SP

Wide-Area GNSS Interference Monitoring with CYGNSS GNSS-R Delay-Doppler Noise Floor Observations

Ji-Hyeon Shin , Pyo-Woong Son This is my paper

Pith reviewed 2026-05-15 16:00 UTC · model grok-4.3

classification 📡 eess.SP
keywords GNSS RFICYGNSSDDM noise floormaximum aggregationinterference monitoringspaceborne detection
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The pith

Replacing the mean with the maximum of four co-temporal DDM noise-floor values improves GNSS RFI detection from CYGNSS observations.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

This paper shows that existing CYGNSS analyses using mean or kurtosis of DDM noise floors miss some interference because ground RFI affects only certain channels depending on antenna orientation. By using the maximum of the four simultaneous values instead, channel-specific anomalies are preserved. A 41 dB threshold is set from reference data, and verification with multi-satellite concurrence over 10 seconds reduces false alarms. Tests in White Sands and Middle East demonstrate higher detection rates than previous methods.

Core claim

The paper claims that the maximum of four co-temporal DDM noise-floor values from CYGNSS provides a better statistic for detecting GNSS RFI than the mean, because it accounts for channel-dependent exposure from different antenna orientations. This enables a simple 41 dB threshold for detection, which when combined with 10-second multi-satellite verification, identifies interference in documented test areas and persistent RFI zones more effectively than mean-based or kurtosis-based approaches.

What carries the argument

Maximum aggregation of the four co-temporal DDM noise-floor values, which prevents dilution of anomalies present in only one or two channels due to viewing geometry.

Load-bearing premise

That the empirically chosen 41 dB threshold and the 10-second multi-satellite verification criteria remain effective outside the two tested regions and do not produce excessive false positives from natural signal variations or antenna effects.

What would settle it

A controlled experiment observing CYGNSS data during a known GPS jamming event in a third location and checking if detections align with ground reports without over-flagging clean areas.

Figures

Figures reproduced from arXiv: 2603.04813 by Ji-Hyeon Shin, Pyo-Woong Son.

Figure 5
Figure 5. Figure 5: Hourly averages of two epoch-wise statistics computed from the four simultaneous DDM noise-floor values—the four￾channel mean and the four-channel maximum—over the Middle East on 13 June 2025. B. Threshold-Based Candidate Flagging The maximum-based aggregation defined above provides a channel-selective summary of the four simultaneous observations. Candidate RFI events are then identified by thresholding t… view at source ↗
Figure 6
Figure 6. Figure 6: DDM noise-floor distributions in two reference environments expected to contain little or no RFI: the Pacific Ocean and the Amazon rainforest. The dashed lines indicate the 40 dB and 41 dB thresholds used to examine the trade-off between sensitivity and non-interference exceedances. TABLE I SUMMARY STATISTICS OF REFERENCE-ENVIRONMENT NOISE-FLOOR DISTRIBUTIONS USED FOR THRESHOLD SETTING Region Total Samples… view at source ↗
Figure 8
Figure 8. Figure 8: Representative abnormal DDMs from May 14 [PITH_FULL_IMAGE:figures/full_fig_p008_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Time-sequential DDMs detected exclusively by the proposed method on May 2. The upper panel shows a jammer geometry that places both nadir antennas in a relatively low-gain viewing direction toward the interference source. The lower panel shows four consecutive DDMs over approximately 2.0 s, in which a weak interference signature becomes progressively more visible as the observation geometry evolves [PITH_… view at source ↗
Figure 10
Figure 10. Figure 10: Daily RFI flag counts over the Middle East from May 1 to 24, 2025, for the kurtosis [PITH_FULL_IMAGE:figures/full_fig_p009_10.png] view at source ↗
Figure 12
Figure 12. Figure 12: Representative atypical abnormal DDMs over the Middle East detected by the proposed method. [PITH_FULL_IMAGE:figures/full_fig_p010_12.png] view at source ↗
read the original abstract

Delay-Doppler Map (DDM) noise-floor observations from the Cyclone Global Navigation Satellite System (CYGNSS) constellation provide a practical means for spaceborne detection of GNSS radio frequency interference (RFI). Existing CYGNSS analyses use NASA's kurtosis-based flag product or mean aggregation of the four simultaneous DDM noise-floor values at each epoch. However, these DDMs are formed from different reflected GNSS signals received through two nadir antennas with different orientations. Thus, ground-based RFI may raise only some channel noise floors, depending on antenna gain and viewing geometry. Mean aggregation can dilute the strongest anomaly with unaffected channels, causing missed detections. This paper replaces the mean with the maximum of four co-temporal DDM noise-floor values. This statistic preserves channel-level anomalies and accounts for channel-dependent exposure. A practical 41 dB threshold is established using low-RFI reference regions and documented or persistent interference environments, enabling simple detection without image-level classification or raw intermediate-frequency processing. To reduce isolated false alarms, a verification stage uses multi-satellite concurrence and temporal persistence over a 10 s window. The method is evaluated using CYGNSS Level 1 data from May 2025 over the White Sands Missile Range, where NOTAM-announced GPS jamming tests provide documented interference conditions, and the Middle East, where persistent RFI has been reported. In the White Sands case, the proposed method detected RFI on three dates where the mean-based method produced negligible detections. In the Middle East, it flagged 62% of observed epochs, compared with 46% for the mean-based method and 33% for the kurtosis-based method. These results show that maximum-based aggregation offers a simple, lightweight improvement over existing CYGNSS DDM noise-floor methods.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The manuscript proposes replacing mean aggregation of four co-temporal CYGNSS DDM noise-floor values with their maximum to detect GNSS RFI, since ground-based interference may affect only some channels depending on antenna orientation and geometry. A fixed 41 dB threshold is set from low-RFI reference regions and documented high-RFI environments, followed by a 10 s multi-satellite persistence verification to suppress isolated false alarms. Evaluation on May 2025 Level-1 data over White Sands (NOTAM jamming tests) and the Middle East (reported persistent RFI) shows the max-based method detects interference on three additional White Sands dates and flags 62 % of epochs versus 46 % (mean) and 33 % (kurtosis).

Significance. If the empirically chosen threshold and persistence rule prove robust, the approach supplies a simple, lightweight improvement to existing CYGNSS DDM-based RFI monitoring that preserves channel-level anomalies without raw IF processing or image classification. Credit is due for grounding the evaluation in independently documented interference events (White Sands NOTAM tests) rather than purely synthetic data.

major comments (2)
  1. [Threshold selection and validation] Threshold selection section: the 41 dB value and 10 s verification window are derived by inspecting the same low-RFI reference regions and the two test domains used for performance reporting. No sensitivity sweep, cross-validation across threshold values, or hold-out evaluation on a third geographic region is presented, so the reported gains (three extra White Sands detections, 62 % vs. 46 % vs. 33 %) remain conditional on the parameter-tuning distribution.
  2. [Evaluation results] Middle East evaluation: the 62 % detection rate is compared against mean- and kurtosis-based baselines, yet the ground-truth label for each epoch rests on prior reports of persistent RFI rather than contemporaneous independent confirmation. This limits the strength of the quantitative superiority claim.
minor comments (2)
  1. [Methods] Clarify in the methods section exactly which four DDM noise-floor channels (antenna 1/2, left/right polarization) enter the max operation and how their individual calibration is handled.
  2. [Discussion] Add a brief statement on expected false-positive behavior under ionospheric scintillation or surface-reflectivity extremes, even if only qualitative.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive comments and the positive assessment of the manuscript's practical contribution. We address each major comment below and outline revisions that strengthen the validation without altering the core claims.

read point-by-point responses

  1. Referee: [Threshold selection and validation] Threshold selection section: the 41 dB value and 10 s verification window are derived by inspecting the same low-RFI reference regions and the two test domains used for performance reporting. No sensitivity sweep, cross-validation across threshold values, or hold-out evaluation on a third geographic region is presented, so the reported gains (three extra White Sands detections, 62 % vs. 46 % vs. 33 %) remain conditional on the parameter-tuning distribution.

    Authors: We agree that the threshold and persistence parameters were informed by the same reference and test regions, which limits claims of full independence. In the revised manuscript we will add a dedicated sensitivity subsection that sweeps the threshold from 38–44 dB and the persistence window from 5–15 s, reporting detection rates on the White Sands NOTAM dates for each combination. We will also clarify that the low-RFI reference regions are geographically separate from both White Sands and the Middle East test areas. These additions will quantify how detection performance varies with parameter choice and will include a brief cross-validation note using an additional low-RFI region not used in the original tuning. revision: yes

  2. Referee: [Evaluation results] Middle East evaluation: the 62 % detection rate is compared against mean- and kurtosis-based baselines, yet the ground-truth label for each epoch rests on prior reports of persistent RFI rather than contemporaneous independent confirmation. This limits the strength of the quantitative superiority claim.

    Authors: We acknowledge that the Middle East labels derive from prior published reports rather than contemporaneous independent measurements, which is a genuine limitation for absolute performance claims. In revision we will add an explicit discussion of this constraint in the evaluation section, stating that the 62 % figure is a relative improvement under the same labeling assumptions used for the mean and kurtosis baselines. We will emphasize that the primary quantitative evidence remains the White Sands NOTAM dates, where interference epochs are independently documented, and will note that contemporaneous ground truth is rarely available for persistent RFI regions. No new data source is introduced, but the text will be revised to avoid overstating absolute detection rates. revision: partial

Circularity Check

0 steps flagged

No circularity; max aggregation and empirical threshold are direct choices, not reductions by construction

full rationale

The paper's central steps are (1) replacing mean with max of four co-temporal DDM noise floors to preserve channel anomalies and (2) setting a 41 dB threshold from low-RFI reference regions plus documented interference environments, followed by multi-satellite verification. These are presented as practical, data-driven choices rather than derived quantities. No equations appear that would make the detection statistic or threshold equivalent to the input data by construction. Performance figures (White Sands dates, 62 % vs 46 % vs 33 %) are reported on the evaluated regions after threshold establishment from references, without any self-citation load-bearing step or fitted-parameter renaming. The derivation chain is therefore self-contained and non-circular.

Axiom & Free-Parameter Ledger

1 free parameters · 1 axioms · 0 invented entities

The central claim rests on one empirically set threshold and a domain assumption about channel-dependent RFI exposure; no new physical entities are introduced.

free parameters (1)
  • 41 dB threshold = 41 dB
    Chosen using low-RFI reference regions and documented interference environments to enable simple detection
axioms (1)
  • domain assumption Ground-based RFI may raise only some of the four co-temporal DDM noise floors depending on antenna gain and viewing geometry
    Invoked to explain why mean aggregation dilutes anomalies while maximum preserves them

pith-pipeline@v0.9.0 · 5632 in / 1401 out tokens · 45506 ms · 2026-05-15T16:00:27.626726+00:00 · methodology

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Reference graph

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