Light Signals of Opportunity (LSOOP)

• LSOOP is the opportunistic use of existing optical signals, such as ambient or infrastructure-provided light, for sensing and communication.
• It differs from conventional methods by using unmodified light sources without added modulation hardware, thus reducing system cost while posing calibration challenges.
• Applications of LSOOP include indoor positioning, passive remote sensing, and transient astronomy, where ambient signal characteristics enable precise measurements.

Searching arXiv for recent and directly relevant papers on Light Signals of Opportunity and adjacent opportunistic optical/SoOp topics. I’m retrieving relevant arXiv records to ground the article in recent literature. Light Signals of Opportunity (LSOOP) denotes the opportunistic use of existing optical, optically accessible, or externally provided signal sources for sensing, positioning, communication, and observation, rather than relying exclusively on dedicated transmitters. In the recent literature, the term is explicit in unmodulated Visible Light Positioning (uVLP), where ordinary illumination sources are treated as localization signals, and it is closely aligned with broader Signals of Opportunity (SoOp) practice in passive reflectometry and externally triggered observation. Within that broader framing, LSOOP encompasses unmodified indoor luminaires, satellite communication emissions reused for bistatic remote sensing, transient astrophysical alerts converted into observing schedules, and adjacent active optical infrastructures whose emissions can plausibly function as opportunity sources under favorable geometry and observability constraints (Alijani et al., 17 Jul 2025, Arumugam et al., 2024, Wistrand et al., 2023, Carrasco-Casado et al., 2017).

1. Conceptual scope and differentiation

The most explicit LSOOP formulation in the provided literature appears in uVLP, which uses unmodulated or unmodified illumination sources—especially conventional LEDs, but also fluorescent lamps, compact fluorescent lamps, and ambient light such as daylight or sunlight—without adding modulation hardware, synchronization circuitry, or altering the lighting infrastructure (Alijani et al., 17 Jul 2025). This distinguishes LSOOP from conventional modulated visible-light positioning, where luminaires are retrofitted so that each LED becomes explicitly distinguishable at the receiver. That retrofit can create a three-way tension among deployment cost, operational complexity, and illumination efficiency. The survey literature states that FDMA schemes can halve effective radiant flux and that polarization-based VLP incurs at least $50\%$ loss; mitigation by reduced amplitude swing, increased duty cycle, or return-to-one coding introduces corresponding penalties in SNR, waveform fidelity, or the strength of discriminative frequency components (Alijani et al., 17 Jul 2025).

A second branch of the concept appears in passive remote sensing. The soil-moisture reflectometry work using Rydberg atoms is directly aligned with the broader SoOp paradigm because the receiver does not transmit its own illumination, but instead exploits an existing satellite communication signal—XM satellite radio—to infer a geophysical variable (Arumugam et al., 2024). In that setting, the “opportunity” lies in the availability of persistent, externally transmitted signals with known spectral structure. A third branch appears in transient astronomy: EUSO-SPB2 treats astrophysical alerts from GCN, TNS, and ATel as external opportunities that justify repointing a Cherenkov telescope to search for upward-going optical Cherenkov emission from tau-neutrino-induced air showers (Wistrand et al., 2023). These cases are operationally different, but they share the same organizing idea: the useful signal is not scheduled, shaped, or owned end-to-end by the receiving system.

The literature also defines conceptual boundaries. Some optical systems are best classified as adjacent to LSOOP rather than direct instances of it. Event-camera tracking of coded 850 nm LED beacons is an intentional active-light infrastructure method, not a passive use of uncontrolled lighting (Arnim et al., 2023). Likewise, spacecraft visible-light downlinks and inter-satellite VLC links are designed communications sources, although their wide beams, repeated availability, and public observability make them plausible sources of opportunity for secondary sensing or calibration uses (Huang et al., 2017, Amanor et al., 2018).

2. Signal classes, receiver families, and observables

A useful organizing structure is the taxonomy proposed for uVLP, which classifies systems by receiver type—intensity-based versus imaging-based—and by separation strategy—demultiplexed versus undemultiplexed (Alijani et al., 17 Jul 2025). Intensity-based receivers include photodiodes, ambient light sensors, solar cells, and spectral sensors. Imaging-based receivers include cameras, CMOS, and CCD sensors. Demultiplexed methods attempt to separate or identify individual sources without active modulation, often through characteristic frequency, spectral signature, or visual distinctiveness. Undemultiplexed methods treat the composite light field itself as the observable and rely on fingerprinting, probabilistic filtering, or learned embeddings.

Regime	Source class	Typical observable
uVLP	Conventional LEDs, FL/CFL, ambient light	RSS, spectra, characteristic frequency, images
Passive reflectometry	XM satellite radio in the S band	Direct/reflected correlation, scattering coefficient
Alert-driven observation	GCN, TNS, ATel transient alerts	Time-sensitive visibility and pointing opportunities
Active optical adjacencies	SOTA downlinks, visible LED spacecraft links, VLC ISLs	Beam footprints, received power, polarization, trackable optical emissions

The measurement primitives differ accordingly. For light-intensity methods, the survey begins from the inverse-square law,

$E=\frac{I}{d^2},$

and Lambert’s cosine law,

$I_\theta = I_0\cos\theta,$

then builds composite received power models with line-of-sight and non-line-of-sight terms. In undemultiplexed settings, the total measurement is

$RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$

which is then mapped to location through fingerprints, probabilistic models, or fusion with inertial sensing (Alijani et al., 17 Jul 2025).

Imaging-based LSOOP methods use source geometry, ceiling-fixture shape, radiance textures, and rolling-shutter aliasing. The camera response to temporal flicker is modeled by a sinc envelope,

$$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$

which permits extraction of aliased characteristic frequencies from ordinary cameras even when the true source flicker lies well above the nominal frame rate (Alijani et al., 17 Jul 2025). This is one of the distinctive methodological features of LSOOP: discriminative temporal structure may be present even when it was never intentionally engineered for positioning.

Adjacent active optical systems illustrate the engineering envelope within which opportunity use may become feasible. SOTA provided repeated LEO optical downlinks at $976$ nm and $1549$ nm, with beam divergences of $500~\mu\text{rad}$ and $223~\mu\text{rad}$, more than one hundred successful links, and polarization-preservation measurements showing degree of polarization near $100\%$ for powers over $E=\frac{I}{d^2},$0 (Carrasco-Casado et al., 2017). A proposed visible-light spacecraft downlink uses $E=\frac{I}{d^2},$1 nm LEDs with $E=\frac{I}{d^2},$2 beam divergence and predicts apparent visual magnitude around $E=\frac{I}{d^2},$3, explicitly positioning the system as a backup telemetry beacon or high-throughput link (Huang et al., 2017). These are not unmodulated sources, but they demonstrate how source geometry, observability, and receiver burden shape whether an optical emission can later be reused opportunistically.

3. Mathematical and algorithmic foundations

LSOOP inherits its mathematical foundations from three overlapping traditions: optical propagation and photometry, correlation-based SoOp estimation, and state-space inference under nuisance parameters.

For optical positioning, the central models are Lambertian channel gain, reflected-path contributions, and receiver response. The survey formalizes both LoS and NLoS terms, receiver filter and concentrator gains, and the dependence of received power on incidence and irradiance angles (Alijani et al., 17 Jul 2025). In practice, these models support several inference regimes: direct trilateration from demultiplexed source amplitudes, probabilistic filtering from composite light fields, and image-plane geometry recovery from ceiling fixtures treated as landmarks.

For passive reflectometry, the Rydberg-atom soil-moisture work translates classical SoOp processing into an atomic receiver architecture. A direct/reference signal is acquired with a conventional chain pointed at the transmitter, while the reflected/scattered signal is acquired by the Rydberg system pointed toward the specular reflection zone. The digital cross-correlation is defined as

$E=\frac{I}{d^2},$4

and the correlation processing gain is written as

$E=\frac{I}{d^2},$5

The soil-moisture retrieval then uses the calibrated empirical model

$E=\frac{I}{d^2},$6

with direct inversion

$E=\frac{I}{d^2},$7

This is not an optical light-field model, but it is methodologically central to LSOOP because it shows how externally transmitted signals can be converted into geophysical observables through direct-plus-reflected geometry, correlation processing, and calibrated inversion (Arumugam et al., 2024).

A broader estimation-theoretic SoOp line addresses asynchronous beacons and nuisance clock parameters. In that framework, each clock is modeled as

$E=\frac{I}{d^2},$8

and modified Bayesian CRLB analysis shows that clock offsets can be structurally eliminated while clock skew degrades Fisher information (Leng et al., 2013). A separate LEO SoOp navigation line estimates recurring symbols directly from partially known Starlink downlinks, collects Doppler measurements over a $E=\frac{I}{d^2},$9 s interval, and computes a least-squares PVT solution with approximately $I_\theta = I_0\cos\theta,$0 m positioning error after a post-fit refinement (Zanirato et al., 6 Feb 2026). Although RF rather than optical, this suggests a directly relevant methodological analogue for LSOOP whenever recurring optical structure must be learned from data rather than prescribed by a dedicated beacon.

4. Application domains

Indoor positioning is the most developed explicitly optical LSOOP application. The uVLP literature surveyed in 2025 spans room-level classification, meter-scale trajectory support, and decimeter-to-centimeter localization depending on receiver type and demultiplexing capability. Reported examples include room-level accuracy up to $I_\theta = I_0\cos\theta,$1 and $I_\theta = I_0\cos\theta,$2, average error about $I_\theta = I_0\cos\theta,$3 m, dynamic corridor average $I_\theta = I_0\cos\theta,$4 m, median $I_\theta = I_0\cos\theta,$5–$I_\theta = I_0\cos\theta,$6 m in image-based settings, and demultiplexed CF-based performance such as $I_\theta = I_0\cos\theta,$7 cm $I_\theta = I_0\cos\theta,$8, $I_\theta = I_0\cos\theta,$9 cm $RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$0, $RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$1 cm $RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$2, and around $RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$3 cm median in favorable setups (Alijani et al., 17 Jul 2025). These results make clear that the accuracy frontier is not set by “light” alone, but by source separability, receiver bandwidth, orientation handling, and the extent to which nuisance variability can be fused with IMU, PDR, or probabilistic filtering.

Passive remote sensing provides a very different application profile. In the Rydberg-atom study, the opportunistic illuminator is XM satellite radio in the S band, specifically $RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$4–$RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$5, and the cesium system is tuned near the $RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$6 transition at $RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$7 with off-resonance of about $RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$8–$RSS_{\text{total}}=\sum_{k=1}^{M} RSS_k,$9 (Arumugam et al., 2024). The lab soil-moisture experiment used dry sand at $$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$0 VSM, increased to $$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$1, $$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$2, and visible saturation at $$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$3, and reported inversion error $$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$4 over this range. In outdoor tests, dynamic retrieval during repeated watering cycles showed fitted percolation time constants increasing to $$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$5 minutes near saturation, and over open terrain the Rydberg-derived soil-moisture time series closely matched classical reflectometry retrieval. The importance of this work to LSOOP lies less in the specific hydrologic target than in the receiver physics: a passive opportunistic sensing chain can be built around a tunable atomic sensor rather than a conventional band-specific microwave front end.

Transient astrophysics offers an operational rather than photometric instance of LSOOP. EUSO-SPB2’s Cherenkov Telescope has field of view $$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$6 in altitude and $$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$7 in azimuth, full payload azimuth rotation $$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$8, and CT tilt range $$|H(f,t_e)|=\left|\mathrm{sinc}\left[f(t_e+t_r)\right]\right|,$$9; in very-high-energy neutrino observation mode the altitude is fixed at $976$0 (Wistrand et al., 2023). A nightly run offers about $976$1–$976$2 hours of operation, individual targets are visible for about $976$3 minutes to $976$4 hour $976$5 minutes, and only $976$6 or $976$7 sources can usually be scheduled. The system continuously updates a catalog from GCN, TNS, and ATel, ranks source classes in a tiered priority scheme, computes when each target crosses the field of view, and allows human-in-the-loop insertion of newly arriving high-priority alerts. In LSOOP terms, this is a full operational architecture for externally triggered, geometry-constrained optical follow-up.

5. Infrastructure, scalability, and deployment regimes

A recurrent theme in the literature is that opportunity use depends strongly on infrastructure designed for other purposes. SOTA is a historical example of a repeatedly observed spaceborne optical transmitter with known orbit, multiple wavelengths, documented pointing behavior, and published pass-level performance. It achieved over one hundred successful links, supported up to $976$8-Mbit/s downlinks using two different wavelengths and apertures, and enabled interoperability with external ground stations in France and Germany (Carrasco-Casado et al., 2017). Its narrow beams and beacon-assisted acquisition constrain passive observability, but its long operational lifetime, multi-site reception, and polarization-stable downlinks make it a credible optical source for atmospheric, calibration, and network studies when geometry permits.

Other active optical architectures are even more explicitly LSOOP-adjacent. A proposed small-spacecraft visible-light system uses a $976$9 nm LED array, a $1549$0 downlink divergence, and PV cells as an omnidirectional optical uplink receiver; the design is presented as a backup telemetry beacon or high-throughput link (Huang et al., 2017). For short-to-medium inter-satellite links, LED-based visible-light communication among small satellites has been analyzed with Fraunhofer-line filtering and IM/DD schemes; a quantitative design point is $1549$1 over $1549$2 with $1549$3 optical transmit power using DPIM and about $1549$4 receiver bandwidth at $1549$5 (Amanor et al., 2018). These systems are intentional emitters, yet they illustrate how wide beams, known wavelengths, and spectral niches can enlarge the set of observers able to exploit a signal.

At larger scale, heliophysics communications is moving toward shared optical infrastructure rather than mission-specific links. A 2023 strategy paper argues that optical communications can provide up to $1549$6 the data rate of traditional RF frequencies up to Ka-band, that the same volume may be downlinked in just one day per week rather than daily under some mission assumptions, and that the only way to guarantee timely space weather warnings with a target of $1549$7 minutes latency is through space relays in MEO or GEO orbits, a strategy which also includes optical communications (Shelton et al., 2023). The same paper recommends heterogeneous optical ground infrastructure: commercial sub-$1549$8-meter OGS up to lunar ranges, $1549$9-meter telescopes for L1/L2 and $500~\mu\text{rad}$0 Mbps cases, $500~\mu\text{rad}$1-meter assets for L4/L5, and hybrid RF/optical DSN assets for Mars-like ranges. For LSOOP, this suggests that future opportunity use may be conditioned less by individual sensors than by the presence of interoperable, shared, multi-mission optical ecosystems.

A further extension is the use of optical intelligent reflecting surfaces. The 2025 OIRS paper models an OGS $500~\mu\text{rad}$2 HAP $500~\mu\text{rad}$3 OIRS $500~\mu\text{rad}$4 user architecture for blocked urban links, with fixed-gain AF relaying at the HAP and end-to-end SNR

$500~\mu\text{rad}$5

Its key contribution is a tractable approximation for Hoyt-distributed geometric and misalignment losses on the reflected optical path, together with closed forms for outage probability, BER, and capacity (Shang et al., 3 Nov 2025). While the paper is a communications study, it is directly relevant to LSOOP because it formalizes when indirect reflected light paths remain usable and which impairments—especially OIRS and receiving-lens fluctuations—dominate reflected-path reliability.

6. Limitations, misconceptions, and research directions

The main limitation running across LSOOP work is that opportunistic use does not eliminate modeling burden; it displaces it. uVLP removes transmitter modulation hardware, but it increases dependence on source identification without explicit IDs, device heterogeneity, orientation sensitivity, ambient-light robustness, and calibration or fingerprint-map maintenance (Alijani et al., 17 Jul 2025). Passive reflectometry removes the need for active illumination, but retrieval may remain calibrated and empirical; the Rydberg soil-moisture demonstration assumes roughness is constant, vegetation is largely absent, and practical broad-spectrum use still depends on external antennas, LNAs, coax, and a classical reference chain (Arumugam et al., 2024). Space optical adjacencies expand observability, but wide-beam systems still confront weather, duty-cycle, and acquisition constraints, while narrow-beam systems sharply limit passive interception (Carrasco-Casado et al., 2017, Huang et al., 2017).

A related misconception is that any optical or light-emitting system automatically qualifies as LSOOP. The event-camera beacon system with $500~\mu\text{rad}$6 nm LEDs, $500~\mu\text{rad}$7-bit fixed-length frames, throughput $500~\mu\text{rad}$8 bps, and tracking/decoding loops is an enabling active optical infrastructure, not a passive opportunistic-light method, because it depends on purpose-built beacons, known blinking frequency, and predefined frame format (Arnim et al., 2023). Conversely, some conceptually striking signaling papers are not practically relevant to LSOOP at all. The axiomatic special-relativity result that hypercomputation in SR is possible if and only if faster-than-light signals exist studies superluminal signaling bodies rather than ordinary light, and the paper explicitly does not provide an optical architecture, opportunistic ambient-light method, or experimentally grounded light-based system (Németi et al., 2012).

The research directions proposed in the literature are comparatively consistent. For uVLP, the most emphasized paths are hybrid modulated-plus-unmodulated deployments, tighter IMU/PDR fusion, broader use of spectral sensing, improved machine-learning pipelines for demultiplexing and fingerprinting, smartphone-centric adaptation, and RIS-assisted uVLP (Alijani et al., 17 Jul 2025). For passive SoOp remote sensing, the roadmap is toward multi-frequency opportunistic sensing of coupled hydrology, broadband reflector dishes coupled to vapor cells, and eventual satellite-based broad-spectrum receivers (Arumugam et al., 2024). For optical infrastructure, the open agenda includes CCSDS-interoperable multi-mission ground networks, DTN-enabled opportunistic path use, hybrid RF/optical relays, and deployment of $500~\mu\text{rad}$9–$223~\mu\text{rad}$0 meter optical ground stations as reusable infrastructure (Shelton et al., 2023). A plausible synthesis is that LSOOP will remain heterogeneous: some systems will exploit ambient or unmodified sources directly, while others will emerge from existing communications, alerting, or relay infrastructures whose emissions become valuable to secondary observers only after those ecosystems are in place.