UAP Dish Sentinel Network Extension for Passive Detection and Tracking of Unidentified Aerial Phenomena (UAP) Using Consumer Ku-band Satellite Infrastructure

UAP Dish Sentinel Network Extension for Passive Detection and Tracking of Unidentified Aerial Phenomena (UAP) Using Consumer Ku-band Satellite Infrastructure

DOI:


John Stephen Swygert, Cumberland, MD 21502, USA


December 02, 2025

Abstract

This paper extends the Dish Sentinel Network (DSN) meteorological baseline established in Swygert (2025, doi:10.5281/zenodo.17790267) into a continental-to-global passive bistatic radar capable of detecting and tracking Unidentified Aerial Phenomena (UAP). The same 22 + million fixed Ku-band consumer satellite dishes already monitoring weather-induced attenuation are shown to be sensitive to brief (5–120 s), non-meteorological forward-scatter and micro-attenuation events caused by discrete reflective objects crossing the narrow, high-elevation beam.

With only open-source software upgrades and optional low-cost SDR hardware, the existing DSN infrastructure becomes the densest civilian sky-surveillance array ever deployed. Multi-station time-difference-of-arrival (TDOA) and Doppler triangulation yield real-time 3-D tracks with 0.5–3 km accuracy across the United States and comparable performance wherever fixed Ku-band direct-broadcast satellites are in widespread use.Keywords: UAP detection, passive bistatic radar, forward scatter, opportunistic illuminators, crowdsourced sensing, Ku-band propagation, open-source science, satellite dish repurposing

1. Introduction

Swygert (2025) demonstrated that consumer satellite television dishes function as passive slant-path atmospheric probes for severe convective wind events. The identical receive geometry—fixed, high-gain antennas pointed 20–45° elevation toward geostationary satellites—also makes each dish an inadvertent passive radar receiver using continuous-wave illuminators of opportunity. This follow-on work adds only software and optional hardware to transform the meteorological DSN into a continuously operating UAP surveillance network.

2. Physical Principles and Sensitivity

Ku-band signals (10.7–14.5 GHz) from geostationary satellites illuminate a ≈1.5° conical volume extending from the surface to >500 km altitude. Objects with radar cross-section ≥ –25 dBsm (metallic sphere ≈ 6–8 cm diameter at typical consumer LNB noise figure and 60–90 cm dish gain) produce detectable forward-scatter perturbations of 0.5–4 dB lasting 5–120 seconds.

Fast-moving targets (200–3000 m s⁻¹) generate unambiguous Doppler shifts of 50 Hz to >12 kHz, resolvable with 1-second coherent integration using inexpensive SDRs.

3. Upgrade Tiers for Existing DSN Nodes

Level 0 – pure software (zero added cost)

Baseline StormScout app flags events <180 s, >2.5 dB depth, no local precipitation (GOES-ABI/MRMS cross-check).Level 1 – $20–40

RTL-SDR v4 connected to LNB IF; 2.4 MS/s IQ streamed to GNU Radio flowgraphs (repository provided) for real-time Doppler spectrum and peak reporting.Level 2 – $120–280

Dual-channel coherent SDR (KrakenSDR or LimeSDR Mini) + small reference omni → direct bistatic range and single-station velocity vector.All code: MIT licence, github.com/DishSentinelNetwork/StormScout-UAP (maintained fork of the meteorological code base).

4. Network-Scale Performance (Back-of-the-Envelope)

Typical U.S. dish spacing in suburban/rural areas is 5–30 km. With GPS-disciplined 1 ms timing and 2.4 MS/s IQ synchronisation:

  • Three stations separated by 40–80 km yield horizontal GDOP ≈ 1–3 at 100 km range → positional accuracy 500 m – 2 km.

  • Vertical accuracy 1–4 km (worse due to near-common elevation angles).

  • Doppler resolution ≈ 15 Hz (1 s integration) → velocity error <30 m s⁻¹ with three or more nodes. Hypothetical example: a target at 20 km altitude moving 800 m s⁻¹ due east crossing beams near Pittsburgh would trigger Level-1 nodes in a 300 km swath within 15 s; four or more coincident reports produce a confirmed track within 25–40 s of first detection.

5. Sensitivity and Limitations by UAP Class

The DSN-UAP extension is primarily sensitive to:

  • Fast-transiting metallic or plasma-containing objects (200–3000+ m s⁻¹) at 1–100 km altitude

  • Mid-altitude reflective spheres, discs, or cylinders ≥ 6–10 cm RCS

  • Objects exhibiting abrupt velocity/direction changes resolvable in Doppler time series It is poorly suited to very slow (<50 m s⁻¹) or extremely low-altitude (<500 m) targets masked by ground clutter and is blind to purely emissive (non-reflective) phenomena.

6. De-confliction, Data Integrity, and False-Alarm Mitigation

Automated exclusion layers (open APIs with local fallbacks):

  • ADS-B, OpenSky, FlightRadar24

  • Satellite passes (Celestrak two-line elements)

  • High-altitude balloon registries Node firmware cryptographically signs every anomaly packet; tracks require ≥3 geographically distinct confirmations within 90 s before public release. Raw IQ data are archived for community audit.

7. Global Scalability and Volunteer Community Model

Every major DBS region (Dish/DirecTV, Sky, DStv, Tata Play, etc.) uses materially identical fixed Ku-band hardware. The code base requires only orbital slot and polarisation tables to operate worldwide. Discarded 60–120 cm offset dishes—millions currently destined for landfills—are explicitly targeted for reactivation.

The author invites the global amateur radio, SDR, and scientific UAP communities (SCU, UAPx, Sky Hub, Enigma Labs, MUFON technical groups, and university radar labs) to fork, regionalise, and harden the system under open-source principles.

8. Conclusion

By adding less than 400 lines of open-source code and optional hardware costing under $300, the meteorological Dish Sentinel Network becomes the largest, continuously operating, civilian passive radar array on Earth—capable of detecting, tracking, and archiving unexplained aerial phenomena at continental scale. The entire capability is placed unconditionally in the hands of the volunteer community for independent verification and evolution.

References

  • Swygert, J. S. (2025). Harnessing Satellite Signal Attenuation for Ultra-Early Severe Storm Warnings.

  • Mercier, F., et al. (2021). Opportunistic use of satellite TV signals. Remote Sens. Environ., 262, 112533.

  • Griffiths, H. D., & Baker, C. J. (2017). Passive coherent location radar systems. In Novel Radar Techniques and Applications.

  • Fraunhofer FHR (2023). SABBIA 2.0: Passive radar using geostationary broadcasting satellites.

  • Kuschel, H., et al. (2019). Passive radar using Ku-band satellite illuminators. IEEE Geosci. Remote Sens. Mag.

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