Quantum Inertial Sensor Patents: Leaders, Trends & White Space 2026
A data-backed look at quantum inertial sensor patents: who is filing, how concentrated the field is, which IPC classes carry the claim density, and where white space remains through 2026.
Top-5 share = the 5 largest assignees ÷ all 61 records in scope (CR5), not the ranked leaders only.
What the quantum inertial sensor patent record actually shows
Quantum inertial sensing turns atom interferometry, coherent spectroscopy and related quantum-coherence effects into navigation, gravity-sensing and timing hardware that does not depend on GPS. The dataset in scope covers 61 published records filed or published between 2015 and the 2026-08-31 cut-off, drawn from a search built around quantum inertial sensor claims and inertial-plus-quantum sensor/detector language. Publication lag of roughly 18 months means the 2025 and 2026 counts understate real filing activity — they will keep rising as more applications publish.
The picture that emerges is a small set of research-heavy assignees holding a majority of the record, a filing curve that only started to climb meaningfully in the last two complete years, and technology claims that spread across navigation, geophysics, computing and timing rather than sitting in one narrow class. That spread matters for anyone deciding where a new filing is likely to clear prior art versus where it will land in dense claim territory.
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Filing trend and technology composition
These figures come directly from the 61 records in scope. Class shares are calculated against the full record count, and because a single record can carry more than one IPC class, the eight class shares below add up to more than 100%.
A late, steep filing curve
Annual filings moved from a single record in 2017 to a peak of 14 in 2025, with 5 recorded so far in 2026 — a partial year given the publication lag. There are not yet four complete post-peak years to support a stated growth rate, so none is given here; the honest read is that activity is recent and still climbing rather than plateauing.
Navigation and gravity sensing lead, but the spread is wide
G01C (distance, navigation and gyroscopes) tops the class list at 19.7% of the 61 records, with G01V (geophysics and gravity surveying), G06F (digital data processing) and G06N (AI-based computing) each at 14.8%. G04F (time-interval measuring), B82Y (nanotechnology), G01S (radar, sonar and positioning) and H04L (digital information transmission) each sit at 11.5%, showing that quantum inertial sensing claims are as much about the software and signal layer as about the sensor itself.
Shares are the percentage of the 61 records in scope. A patent can carry several IPC classes, so the shares add up to more than 100%.
Go deeper on Quantum Sensing & Metrology: Quantum Inertial Sensor Patent Landscape with Eureka
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Try EurekaA representative claim and the most-cited prior art
Coherent spectroscopic methods with extended interrogation times and systems implementing such methods (US10041835B2)
Coherent spectroscopic methods are described, to measure the total phase difference during an extended interrogation interval between the signal delivered by a local oscillator and that given by a quantum system. The method reads out intermediate error signals at the end of successive interrogation sub-intervals, corresponding to the approximate phase difference between the local oscillator and the quantum system, using coherence-preserving measurements, then shifts the local oscillator phase by a known correction value at the end of each sub-interval.Filed by Centre National de la Recherche Scientifique (CNRS), published 2018-08-07.
| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US10991242B2 | Sustained vehicle velocity via virtual private infrastructure | 114 |
| 2 | US20160014403A1 | Flexible display device and computer with sensors and control approaches | 81 |
| 3 | US20160018525A1 | Quantum Imaging for Underwater Arctic Navigation | 45 |
| 4 | US9961337B2 | Flexible display device and computer with sensors and control approaches | 42 |
| 5 | US20140375998A1 | Atom interferometry having spatially resolved phase | 26 |
| 6 | US20150189256A1 | Autostereoscopic multi-layer display and control approaches | 19 |
| 7 | US20190340317A1 | Computer vision through simulated hardware optimization | 18 |
| 8 | CN105674982A | 一种六参数量子惯性传感器及其测量方法 | 16 |
| 9 | US20170356803A1 | Coherent spectroscopic methods with extended interrogation times and systems implementing such methods | 10 |
| 10 | US9175960B1 | Optically dithered atomic gyro-compass | 10 |
Citation counts inside this corpus skew toward older filings simply because they have had more time to be cited — read them as a signal of influence within the searched set, not as a ranking of current technical importance.
Patent titles are shown in the language they were filed in, not translated, so that each record stays verifiable against the original filing — a translated title will not match in Eureka or in any national register. Each row carries its publication number; clicking a row searches Eureka by that number.
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Browse MCP servers →What the concentration and class spread mean for a filer
Three figures from this dataset are worth sitting with before deciding where to file next: how concentrated the leadership is, how recent the real activity is, and how wide the technology spread already is.
A short head, not an open field
The top 5 assignees account for 55.7% of all 61 records in scope, and the top 10 for 73.8%. That leaves a long tail of single- or low-filing entrants competing for the remaining share, which is a harder place to build a defensible position than the numbers alone suggest.
The record is younger than it looks
Filing only reached one record a year as recently as 2017 and did not cross into double digits until 2025's peak of 14. With publication lag of around 18 months, the 2026 count of 5 will rise as more filings clear publication, so the real 2025–2026 window is likely busier than currently visible.
Navigation leads, but only narrowly
G01C claims (distance, navigation and gyroscopes) lead at 19.7% of the 61 records, but G01V, G06F and G06N each sit at 14.8%, and four more subclasses cluster at 11.5%. No single branch dominates the claim space, which points to a technology still being defined across sensing, computing and signal-processing layers at once.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to quantum sensing & metrology: quantum inertial sensor patent landscape, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| Centre National de la Recherche Scientifique (CNRS) | Observatoire de Paris | 8 |
| Centre National de la Recherche Scientifique (CNRS) | INST DOPTIQUE GRADUATE SCHOOL | 8 |
| Observatoire de Paris | INST DOPTIQUE GRADUATE SCHOOL | 8 |
The strongest co-assignee pairings in this dataset link CNRS, Observatoire de Paris and Institut d'Optique Graduate School, each pairing appearing 8 times — a signature of French public-research collaboration rather than corporate joint filing.
Where to take this analysis
The dataset points to a field where a small research-institution cluster holds a majority of the record and the technology claims are still spreading across adjacent classes. Two directions follow from that.
Map the white space before drafting
With claim density split across eight IPC subclasses and no single branch above 20% of records, a new filing has real room to target an under-claimed combination — for instance AI-based signal processing (G06N) paired with gravity sensing (G01V) rather than pure navigation.
Explore white space in EurekaWatch the research-institution cluster
The strongest co-assignee links sit among a small set of French public-research bodies rather than large corporate filers, which changes how licensing and freedom-to-operate conversations should be approached in this space.
Track assignee activity in EurekaQuestions practitioners ask about this field
This dataset covers 61 published records filed or published between 2015 and the 2026-08-31 cut-off, built from a search targeting quantum inertial sensor claims and combined inertial-plus-quantum sensor or detector language. That is the record count in scope for this analysis, not a universal count of every possible related filing, since search scope and classification choices affect what is captured. Because publication lags filing by roughly 18 months, the most recent years understate real activity and will rise as more applications publish.
The ranking returned for this dataset covers 45 assignees, with the leader holding 8 records, fifth place holding 5, and tenth place holding 2. The top 5 combined account for 55.7% of all 61 records in scope, and the top 10 combined for 73.8%, so leadership is concentrated but not held by a single dominant filer. The rest of the ranking is a long tail of entrants with one or two filings each, which is typical of a field still in an early research phase.
Claims cluster most heavily in G01C (distance measurement, navigation and gyroscopes) at 19.7% of the 61 records in scope, followed closely by G01V (geophysics and gravity surveying), G06F (digital data processing) and G06N (AI-based computing), each at 14.8%. G04F (time-interval measuring), B82Y (nanotechnology), G01S (radar, sonar and positioning) and H04L (digital transmission) each sit at 11.5%. Because a record can carry multiple IPC codes, these shares add up to more than 100%, and the spread shows the field spans sensing hardware, signal processing and computing rather than one narrow mechanical category.
Filing activity rose from a single record in 2017 to a peak of 14 in 2025, with 5 recorded so far in 2026. That 2026 figure is a partial-year count depressed by publication lag, so the true 2026 filing level is almost certainly higher once later publications clear. There are not yet four complete post-peak years of data, so a reliable growth rate cannot be stated from this dataset, but the trajectory from 2017 through 2025 is clearly upward.
The IPC composition shows no single class above roughly 20% of the 61 records, and several classes covering AI-based computing, geophysics, timing and radar/positioning sit close together in the 11–15% range. That spread suggests combinations across these classes — such as AI-based signal processing applied to gravity or timing sensors — are less densely claimed than pure navigation-focused filings. Checking the specific claim language and citing patterns in Eureka before drafting is the more reliable way to confirm a gap than relying on class shares alone.
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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.