Time-of-Flight Sensor Interface Patents: Leaders & Trends 2026
- Filing activity peaked in 2019 and has since flattened, with only one filing recorded at the 2022 midpoint despite a decade of activity in this dataset.
- 24 of 25 families sit in G01S, leaving alarm-system, vehicle and AI-pipeline integration claims almost untouched by comparison.
- The most-cited record traces to 2015, meaning the terminology this field still cites was set a decade before the newest granted claim in this set.
Filing growth compares 2021 (2 records) with 2024 (3) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field.
A narrow, interface-specific slice of ToF sensing
This landscape covers patent families that combine time-of-flight or ToF sensor claim language with interface-specific terms — MIPI interface, high-speed depth readout, sensor-processor interface or general data interface — inside IPC classes for optical ranging, image sensor readout circuitry and semiconductor image devices. It is a deliberately narrow cut: sensing physics alone does not qualify a filing here, the claims have to address how depth data moves off the sensor.
Twenty-five families span 2015 to mid-2026, with United States and European filings the two largest receiving offices in the set. The pattern that emerges is a claim space that filled up early, peaked in 2019, and has shown no comparable resurgence since, even accounting for publication lag in the most recent years.
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Filing trend and technology composition
Twenty-five patent families make up this dataset, filed between 2015 and mid-2026 under a search string that pairs time-of-flight sensing terms with interface-specific claim language.
Filings peaked in 2019 and have not recovered
Annual filings rose from 2 in 2017 to a peak of 6 in 2019, then fell back to a single filing at the 2022 midpoint. Publication lag of roughly 18 months means the last one to two years understate true filing activity, but the multi-year decline predates that window.
G01S dominates; supporting subclasses are thin
G01S (radar, sonar and positioning) covers 24 of the records, effectively the entire dataset, with G01C (distance and navigation) a distant second at 5. Image processing (G06T), video communication (H04N), alarm systems (G08B), vehicle integration (B60R), AI computing (G06N) and business-process data handling (G06Q) each appear in single digits, marking them as adjacent rather than core to how this claim space has been filed so far.
Shares are the percentage of the 25 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Time-of-Flight Sensor Interface Engineering with Eureka
This page is one run against one query. Ask Eureka your own question about time-of-flight sensor interface engineering and every answer comes back with the patent numbers behind it.
Try EurekaThe records shaping this claim space
Time-of-flight sensor and system (US12681185B2)
Sony Semiconductor Solutions' granted patent describes a time-of-flight system whose logic circuitry includes a sequencer and a register circuitry with multiple registers for data derived from light-sensing signals, where the sequencer selects between at least two sets of those registers during operation.Granted 2026-07-14 — the newest record in this dataset, and a live constraint on register-level sequencing designs for depth data.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US20180003807A1 | Waveform reconstruction in a time-of-flight sensor | 23 |
| 2 | US20150331092A1 | Waveform reconstruction in a time-of-flight sensor | 21 |
| 3 | US20200018834A1 | High dynamic range for sensing systems and methods | 20 |
| 4 | US20190346540A1 | Permutation of measuring capacitors in a time-of-flight sensor | 13 |
| 5 | US20220021831A1 | Depth pixel having multi-tap structure and time-of-flight sensor including the same | 9 |
| 6 | US9921300B2 | Waveform reconstruction in a time-of-flight sensor | 6 |
| 7 | US11627266B2 | Depth pixel having multi-tap structure and time-of-flight sensor including the same | 4 |
| 8 | EP3594716A1 | High dynamic range for sensing systems and methods | 3 |
| 9 | EP2947477A2 | Waveform reconstruction in a time-of-flight sensor | 3 |
| 10 | US20240068810A1 | Measuring device with TOF sensor | 2 |
Ranked by citation count within the searched corpus; older filings are structurally favored, so read this as a map of influence rather than current commercial weight.
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Browse MCP servers →What the filing pattern tells a filer
Three signals stand out once the 25 families are broken down by year, IPC class and citation weight: a settled core architecture, a thin set of adjacent branches, and citation influence concentrated in a handful of early filings.
Growth has flattened since the 2019 peak
From 2 filings in 2017 to a peak of 6 in 2019, activity fell back to 1 filing at the 2022 midpoint. That trajectory reads as a claim space that filled up early rather than one still being actively contested.
Almost the entire dataset sits in one IPC subclass
G01S (radar, sonar and positioning) covers all but one of the 25 records. Supporting subclasses like G01C, G06T and H04N each appear only a handful of times, marking clear but narrow adjacency.
Influence concentrates in two early waveform patents
The two highest-cited records in this corpus both describe waveform reconstruction in a time-of-flight sensor, cited 23 and 21 times respectively. Their age gives them a citation advantage that newer, equally relevant filings have not had time to accumulate.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to time-of-flight sensor interface engineering, with the prior art for and against each one.
Who is filing, and where the room to move sits
Recent-year momentum shows no assignee in this dataset with a published filing in the latest year, which is expected given publication lag but still leaves the field without a clear current leader. The strongest filing relationship in the set links two assignees on five shared families, pointing to a coordinated or affiliated filing strategy rather than independent parallel work.
One pairing anchors the densest filing cluster
The strongest co-assignee relationship in this dataset links two organisations across five shared families, the largest overlap of any pair here. That concentration suggests a joint development or supply relationship behind a meaningful slice of the dataset.
Filing strategy centers on the US and Europe
United States filings lead at 15 records, with the European Patent Office second at 10. No other office appears at comparable volume in this set, so competitive filing pressure in this niche is effectively a two-office contest.
Two early filings still set the reference terms
The two most-cited records in the dataset, both on waveform reconstruction, carry citation counts well above the rest of the set. New entrants drafting around this space should expect examiners and competitors to keep referencing these two.
| Assignee | Recent year | YoY |
|---|---|---|
| Rockwell Automation Technologies, Inc. | 0 | — |
| Innovative Micro Technology | 0 | — |
| Facebook Technologies, LLC | 0 | — |
| Samsung Electronics Co., Ltd. (Korea) | 0 | — |
| Hexagon Technology Center GmbH | 0 | — |
| Honor Device Co., Ltd. | 0 | — |
| Sony Semiconductor Solutions Corporation | 0 | — |
| SPIREON INC | 0 | — |
Where to take this analysis
The filing and citation patterns above point to specific next steps for a team deciding where to file or who to watch.
Check the interface-layer white space
Alarm-system integration, vehicle-specific packaging and AI-pipeline linkage each show only one or two supporting records, well below the dominant IPC class. That gap is worth testing against a specific product roadmap before assuming it is open.
Explore white space in EurekaTrack the two highest-cited waveform patents
Both top-cited records describe waveform reconstruction in a time-of-flight sensor and set much of the field's reference terminology. Any new filing in the sensing core should be checked against their claim scope first.
Pull citation detail in EurekaWatch the strongest co-filing pair
Five shared families link the dataset's top assignee pair, the densest relationship in this set. Understanding what that pairing is jointly protecting can clarify whether a competing filing needs to route around a coordinated position.
Review assignee relationships in EurekaCommon questions on ToF sensor interface patents
In this dataset, it is a filing that combines direct time-of-flight or ToF sensor claim language with interface-specific terms such as MIPI interface, high-speed depth readout, sensor-processor interface or general data interface, and sits within IPC classes covering optical distance measurement, image sensor readout or semiconductor image devices. That combination narrows the field to the electronics and protocol layer between the sensor die and the host processor, rather than the underlying depth-sensing physics. Filings that describe only the sensing method without addressing how data moves off the chip fall outside this scope.
The dataset shows six filings in 2019, the highest single year, followed by a decline that leaves 2022 at just one filing. This pattern is consistent with an architecture reaching a stable design point: once core waveform reconstruction and readout methods were claimed and cited heavily by later applicants, incentive to file competing interface patents in the same narrow space appears to have dropped. Readers should treat the final one to two years of any trend as understated, since publication typically lags filing by around 18 months.
The most-cited records in this corpus are two waveform reconstruction filings and a high dynamic range sensing patent, each cited well above the rest of the set, followed by a permutation-of-measuring-capacitors filing and a multi-tap depth pixel structure patent. High citation counts inside a search corpus favor older filings simply because they have had more time to be cited, so treat these as markers of technical influence on the field's terminology rather than proof they remain the most commercially relevant today.
The technology composition is heavily concentrated in G01S, with only single-digit representation in adjacent subclasses like alarm systems, vehicle integration, AI-model computing and business-process data handling. That imbalance points to under-claimed integration work: connecting time-of-flight interface data to alarm or safety systems, vehicle subsystems, or AI inference pipelines, rather than new sensing or waveform methods, which are where the dense, highly-cited prior art sits.
The recent-year momentum data shows every listed assignee at zero filings in the latest year, so no single company currently shows fresh, published filing momentum. Historically, the strongest co-filing relationship in the dataset links two of these assignees, suggesting some collaborative or affiliated filing pattern, but the overall picture across 25 families is a modest, fairly distributed set of contributors rather than one dominant filer.
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Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company’s registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.