Security company Leonardo markets SignalTrace, a surveillance system designed to work alongside automatic license plate readers. The technology recognizes groups of consumer devices that regularly move together and associates them with license plate records and time-stamped locations.
According to Leonardo, investigators can search these patterns even when they do not know the specific plate number. The system is a tested and marketed capability, though it is not yet an established police practice. Several SignalTrace devices are installed in Oxon Hill, Maryland, US, and Leonardo's predecessor technology appears on an official New York state, US contract price list.
Four time-and-place points were enough to uniquely identify this percentage of people in a Scientific Reports dataset.
Anonymous signatures and identification risks
Leonardo states that SignalTrace does not identify people and only collects electronic signatures from signals already being broadcast, such as Bluetooth or radio frequency identification tags. These electronic signatures, by themselves, do not disclose a person's identity. Leonardo adds that the output must be corroborated through ordinary investigative methods.
However, police could still determine who likely owns a device by linking its signal to other records. A signal might repeatedly appear with a car registered to one person, outside that person's home, or alongside another device connected to a known subject. Once an officer links a recurring signature to a license plate record or case file, the absence of a name in the original signal offers little protection.
Data that can distinguish or trace a person's identity, alone or with linkable info.
Federal privacy guidance does not limit identifying information to names. The US National Institute of Standards and Technology defines personally identifiable information as data that can distinguish or trace a person's identity, either alone or when combined with linkable information. A study in the journal Scientific Reports examined 15 months of records covering 1.5 million people and found that four time-and-place points were enough to uniquely identify 95% of the people in the dataset. This study did not test SignalTrace.
Legal precedents and social mapping
The US Supreme Court has recognized that phone location records can reveal far more than movement. In Carpenter v. United States, the court concluded that people have a reasonable expectation of privacy in the record of their physical movements. The court extended that reasoning in its June 2026 decision in Chatrie v. United States. In that case, police investigating a bank robbery used a warrant to obtain anonymized location records for phones near the bank, narrowed the list based on movements, and eventually obtained the names of several users. The justices held that obtaining location data constituted a Fourth Amendment search and noted that even short-term monitoring can reveal political, family, and other associations.
The Chatrie ruling does not determine whether police collection of wireless signals detected by SignalTrace would also count as a search. The Chatrie case involved location records, while SignalTrace is designed to detect signals broadcast from nearby devices. SignalTrace simply observes when people are near one another and cannot know why people were close to each other. A device can be borrowed or left in a car, and a roadside sensor could capture someone standing nearby. Even a correct match between a device and a vehicle does not establish who carried it on a particular day.
Leonardo says SignalTrace is designed to develop leads. These leads influence which records officers request and whose movements receive further scrutiny. By the time an investigator attaches a name, the inferred association has already shaped the inquiry. Investigators may no longer need to begin with a known person or vehicle; they can begin with recurring patterns of movement and proximity, then use other records to identify the people connected to them.
A study in the journal Proceedings of the National Academy of Sciences followed 94 participants using phones that recorded Bluetooth proximity and calling patterns. It found that patterns of behavior could accurately classify 95% of reciprocally reported friendships. Proximity outside work and during off-hours played an important role in distinguishing friends from other people who regularly encountered one another. SignalTrace uses a different method and no independent study has shown comparable performance, but the research demonstrates that repeated proximity can reveal social ties. A person might come to police attention because their device repeatedly appeared near a group under investigation.
Leonardo's SignalTrace product page says the system stores electronic fingerprints for later queries and can recognize a vehicle without seeing its license plate. A separate Leonardo product sheet says the technology helps identify suspects through the mix of devices they carry. The patent behind SignalTrace describes targets that may be people or vehicles. It also describes searchable signatures that can be correlated with visual identifiers and used to track a target across locations. An electronic signature can become identifying without containing a name. A phone detected beside the same devices over time may reveal a relationship before the police know who owns it.
