Bidirectional time transfer within a coherent sensor array system

Abstract

Methods and systems for time synchronization of a distributed sensor array system ("distributed system") are described herein. The distributed system comprises multiple sensor nodes that are time-synchronized using a combination of RF signal data and message-based time techniques across multiple communication mechanisms. Time synchronization is performed both internally between components of the sensor nodes and over the air between different sensor nodes. The distributed system further uses multiple layers of standardized and custom synchronization protocols to construct a scalable and potentially zero-hop time transport network. The time synchronization accuracy achieved by the time transport network enables coherence in the distributed system.

Description

Background Art

[0001] A phased array antenna has the unique ability to change the shape and direction of its radiation pattern without physically moving the antenna. The elements within the antenna array are arranged such that the signals transmitted by the individual antennas are added together to provide better gain, directivity, and performance in a specific direction. The time synchronization between the various nodes of a phased array system must be maintained so that all nodes can perform coherent operations within the same coordination interval of the clock. However, conventional phased array systems have drawbacks. They are often expensive to implement, too large in size, require excessive power, operate in a limited frequency range, and / or are overly complex (e.g., having a stringent calibration routine that consumes a significant amount of time (e.g., several months)). Further, the distance between the antenna elements of these systems is limited by the wavelength of the signal being modulated. These and other drawbacks have led to the proposed use of a "distributed" array where the elements can be physically separated. However, distributed arrays impose an extraordinary requirement for time synchronization of the separated elements. It is particularly difficult to maintain synchronization when an array, which can be regarded as a network of sensor "nodes", requires timing information to be achieved over successive hops.

Summary of the Invention

[0002] In one general embodiment, the method may include establishing a zero-hop network architecture between a plurality of sensor nodes via a processor node, each of the plurality of sensor nodes including a dedicated bidirectional time transfer (TWTT) channel. The method may also include designating a master node and a plurality of slave nodes via a processor node, the master node communicating with a dedicated TWTT channel for each of the plurality of slave nodes to form a noiseless timing distribution network. The method may further include distributing a master timing signal from a grandmaster clock via the master node, the grandmaster clock enabling picosecond time synchronization fidelity between the master node and the plurality of slave nodes within the noiseless timing distribution network. Other embodiments of this embodiment include a corresponding computer system, apparatus, and a computer program recorded in one or more computer storage devices, each configured to perform the operation of the method.

[0003] In one general embodiment, a non-transient computer-readable medium may include one or more instructions causing the device to establish a zero-hop network architecture between a plurality of sensor nodes via a processor node, when executed by one or more processors of the device, that each of the plurality of sensor nodes includes a dedicated bidirectional time transfer (TWTT) channel, and that via the processor node, designate a master node and a plurality of slave nodes, that the master node communicates with a dedicated TWTT channel for each of the plurality of slave nodes to form a noiseless timing distribution network, and that via the master node, distribute a master timing signal from a grandmaster clock, that the grandmaster clock achieves picosecond time synchronization fidelity between the master node and the plurality of slave nodes, at least within the noiseless timing distribution network. Other embodiments of this embodiment include a corresponding computer system, apparatus, and a computer program recorded in one or more computer storage devices, each configured to perform the operation of the method.

[0004] In one common embodiment, the system may include one or more processors configured to establish a zero-hop network architecture between multiple sensor nodes via processor nodes, each of the multiple sensor nodes including a dedicated bidirectional time transfer (TWTT) channel. The system may also designate a master node and multiple slave nodes via the processor nodes, with the master node communicating with a dedicated TWTT channel for each of the multiple slave nodes to form a noiseless timing distribution network. In addition, the system may distribute a master timing signal from a grandmaster clock via the master node, which achieves picosecond time synchronization fidelity between the master node and the multiple slave nodes, at least within the noiseless timing distribution network. Other embodiments of this embodiment include a corresponding computer system, apparatus, and computer programs recorded in one or more computer storage devices, each configured to perform the operation of the method.

[0005] Methods and systems for distributed sensor array systems ("distributed systems") with improved time synchronization between sensor nodes in a distributed system are described. Each sensor node is connected (e.g., via wired means or wirelessly) to another sensor node or component of the distributed system, and includes radios such as software-defined radios (SDRs) that facilitate time synchronization between sensor nodes. Although there are many references to SDRs in this specification, the term should be used as an unrestricted example that may refer to analog and / or digital radio devices, sensor nodes, and / or multi-input multiple-output (MIMO) sensor array systems. Similarly, any particular frequency ranges, timing fidelity descriptions, communication standards, and professional association standards included herein are illustrative and unrestricted examples. For example, terms such as "sub-nanosecond" and "picosecond time resolution" refer to possible implementations, and the system is intended to use a wide range of synchronization resolutions to address several application-specific problems (e.g., time alignment of sensor nodes in a coherent phased array). Sensor nodes are configured to share state information with the distributed system so that any received signals or signals transmitted by the sensor node are calibrated and synchronized with each other to synchronize data acquisition across the distributed system. For example, each sensor node synchronizes with a reference node in the distributed system by calculating a time offset between the sensor node and the reference node based on the timestamp of the reception of the calibration signal at the reference node and the corresponding sensor. The data signal received at the sensor node is then "time-aligned" with the data signal received at the reference node based on the time offset. The phase and amplitude of the data signal received at the sensor node may also be aligned with the phase and amplitude of the data signal received at the reference node. Sensor nodes can use known waveforms from transmitting nodes in the distributed system as calibration signals. Other known waveforms may include communication waveforms from other nodes, such as GPS signals, millimeter wave, 60 GHz band, 5G, or 6G communication transmitters. Sensor nodes may also be configured to synchronize with each other using factory-calibrated atomic clocks.Sensor nodes may have the ability to self-organize (e.g., share location information such as latitude, longitude, and altitude via state information) or self-calibrate (e.g., synchronize themselves with a reference node). For example, a distributed system may have location information for a reference node and sensor nodes, which can be used to determine the time difference in the arrival of calibration signals at the sensor nodes relative to the reference node, and which may be used further to determine the time offset between the sensor nodes and the reference node. Sensor nodes may self-calibrate on a scheduled basis using a factory-calibrated atomic clock, calibration signal, or other known waveform before transmitting a probe signal or before receiving a response to a probe signal.

[0006] Such distributed systems solve various problems of conventional phased array systems. In a non-restrictive definition, conventional phased array systems may refer to radar systems in general, large and very large arrays, large arrays with phased array elements, uniform linear arrays, heterogeneous arrays, MIMO sensor array systems, conformal arrays, adaptive / reconfigurable arrays, logarithmic periodic dipole arrays, etc. For example, by synchronizing sensor nodes with a reference node and broadcasting calibration signals using at least one transmitter node to offset multi-node synchronization errors, the disclosed concept can achieve time synchronization accuracy far beyond the scope of conventional phased array systems. In another example, by allowing sensor nodes to self-calibrate, the problem of arduous calibration routines, which can take months in conventional phased array systems whenever temperature, pressure, moisture, or the position of the phased array changes, is solved. In yet another example, by synchronizing each sensor node with a reference node, all sensor nodes are one hop away from the reference node, and therefore time synchronization is not degraded by scaling of the distributed system. In some embodiments, by making the sensor nodes and transmit nodes self-organizing, the transmit nodes do not need to be located in the same place as the sensor nodes, thus preventing the problem of the transmitter exposing the location of the base station / operator / receiver (e.g., in surveillance applications such as radar systems). In some embodiments, by having an SDR, the distributed system can be configured to operate in a wide variety of frequency ranges (e.g., low frequency ranges) that not only serve ultra-long-range and high-speed radar detection and sensing applications but also minimize the size of the required phased array system, which would otherwise be too large or impractical to implement for low-frequency operation.

[0007] The distributed nature of the systems described herein offers several advantages. Distributed systems make the detection of high-speed flying objects much easier without the need to alias Doppler signals. Distributed systems can detect flying objects at much longer distances than conventional radar systems, particularly for a given volume (distributed systems occupy less volume, less weight, and consume less power than conventional phased array systems). Distributed systems are much cheaper and faster to deploy than conventional phased array systems. Distributed systems allow receiver (e.g., sensor nodes) and transmitter nodes to be located far apart and not in the same location (e.g., the transmitter may also be moving), resulting in the transmitter not exposing the receiver's location and solving the counter-stealth problem. Distributed systems provide better angular resolution for a given frequency than conventional phased array systems because sensor nodes can be spaced further apart. Distributed systems offer a new "pass-through" radar capability where the receiver can align directly with the transmitter and is independent of reflection. For example, a sensor node can analyze the backscatter of signals transmitted through a chemical plume to identify the plume's properties (e.g., concentration, composition, relative position, etc.).

[0008] Various other aspects, features, and advantages of the present invention will become apparent through the detailed description of the invention and the accompanying drawings. It should be understood that both the general description above and the detailed description below are examples and do not limit the scope of the invention. As used herein and in the claims, the singular “one,” “one,” and “it” refer to multiple subjects unless the context explicitly indicates otherwise. In addition, as used herein and in the claims, the term “or” means “and / or” unless the context explicitly indicates otherwise. Furthermore, as used herein, “part” refers to a portion or all (i.e., the whole) of a given item (e.g., data) unless the context explicitly indicates otherwise. [Brief explanation of the drawing]

[0009] [Figure 1]This shows a distributed sensor array system consistent with various embodiments. [Figure 2] This is a block diagram of the sensor nodes of the distributed system in Figure 1, consistent with various embodiments. [Figure 3A] Figure 1 shows an example of synchronizing sensor nodes using calibration signals from transmitter nodes in a distributed system, consistent with various embodiments. [Figure 3B] An example of a noiseless time-distributed network using both wired and wireless time transfer channels to synchronize the sensor nodes of the distributed system in Figure 1 is shown, consistent with various embodiments. [Figure 3C] An example of a noiseless time-distributed network that synthesizes a time-synchronization protocol and over-the-air waveform synchronization for synchronizing sensor nodes in the distributed system of Figure 1, consistent with various embodiments, is shown. [Figure 4A] A flowchart illustrating a method for synchronizing sensor nodes in a distributed system with a calibration signal, consistent with various embodiments, is shown. [Figure 4B] A flowchart shows a method for synchronizing time-focused sensor nodes in a distributed system using a high-precision timing protocol (PTP), consistent with various embodiments. [Figure 5A] This is a block diagram illustrating the generation of time-aligned data signals for sensor nodes in a distributed system, consistent with various embodiments. [Figure 5B] This is a block diagram illustrating the generation of time-aligned data signals for sensor nodes in a distributed system, consistent with various embodiments. [Figure 5C] This is a block diagram illustrating the generation of time-aligned data signals for sensor nodes in a distributed system, consistent with various embodiments. [Figure 6] A flowchart shows a method for initializing a bidirectional time transfer protocol that performs time focusing operations using a dedicated transmitter node when synchronizing sensor nodes in the distributed system of Figure 1, consistent with various embodiments. [Figure 7A]This is a block diagram of a passive voltage regulator system implemented using the distributed system shown in Figure 1, consistent with various embodiments. [Figure 7B] This is a block diagram of a successful passive radar target acquisition using the distributed system shown in Figure 1, consistent with various embodiments. [Figure 8] This is a block diagram of a radar system implemented using the distributed system shown in Figure 1, consistent with various embodiments. [Modes for carrying out the invention]

[0010] The following description includes numerous specific details to provide a complete understanding of the embodiments of the present invention for illustrative purposes. However, those skilled in the art will understand that embodiments of the present invention can be practiced without these specific details or with equivalent configurations. In other cases, well-known structures and devices are shown in block diagrams to avoid unnecessarily obscuring embodiments of the present invention.

[0011] The disclosed concept relates to a system that provides a flexible, multi-functional radio frequency (RF) solution by leveraging radio, such as a software-defined radio (SDR) with several time-aligned antenna nodes. For example, the system can provide communications, radar, and electronic intelligence (ELINT) functions in a rapidly deployable software-defined architecture. In some embodiments, the system leverages machine learning algorithms to enable a phased array of SDR antenna elements to mitigate, respond to, and potentially implement RF interference and jamming techniques (e.g., frequency-hopping jamming, spread spectrum jamming, powerful pulsed jamming, smart or adaptive jamming, low probability of interception (LPI) techniques). For example, the system can enable or respond to jamming devices that perform jamming operations by rapidly switching frequencies, making it difficult to adapt conventional static frequency countermeasures. The system can enable or respond to jamming devices that perform jamming operations that spread their energy over a wide range of frequencies, effectively diluting the power of the jamming signal, but affecting a wider set of frequencies. The system can enable or respond to synchronized short bursts of high-power signals that are capable of overwhelming receivers (e.g., systems that rely on highly sensitive detection equipment). The system can analyze the target signal and use or respond to jamming operations that adapt the jamming strategy accordingly. The system can use or respond to jamming operations that mimic legitimate signals to cause disruption, or use selective jamming techniques to target specific communications while leaving others intact. The system can use or respond to jamming operations that use low-power levels of signaling to remain undetected while still effectively disrupting communications. The system is designed to adapt to ongoing advancements in both jamming techniques and beamforming countermeasures used in electronic warfare. The system's ability to rapidly adapt to the changing electronic warfare landscape is designed to counter it by leveraging the integration of advanced technologies such as AI and machine learning.The system can leverage adaptive beamforming techniques to direct a high-gain directional beam towards a target satellite while simultaneously generating a null beam to cancel 5G and / or multispectral interference. These beams can be arbitrarily manipulated in real time to track the satellite's transition across the sky based on pre-known and / or real-time collected orbital parameters. Furthermore, the ability to synchronize multiple antenna nodes provides a technical discriminator that enables the system to implement a scalable processing architecture, distributing the computational overhead of signal processing and adaptive beamforming required to combine groups of subarray elements within a phased array across several processor nodes.

[0012] Figure 1 shows a distributed sensor array system 100 consistent with various embodiments. For example, the distributed sensor array system ("distributed system") 100 may include a plurality of sensor nodes 104a-104n that facilitate the transmission of waveforms as beams in a desired direction. In some embodiments, the distributed system 100 may include any combination of dense and sparse phased array systems (e.g., dense only, sparse only, or a combination thereof). Furthermore, the distributed system 100 can adaptively select an appropriate sensor node configuration based on operating requirements, adversarial operations, and / or changing environmental conditions. Each sensor node may include a radio frequency antenna element. In some non-limiting embodiments, the sensor nodes include an SDR configured to operate over a wide range of radio frequencies (e.g., 3 Hz to 3000 GHz). The distributed system 100 may be implemented in a variety of applications. For example, the distributed system 100 may be implemented as a radar system, as a sonar system, for surveillance in the oil and gas industry for energy discovery, in mining for metal discovery, and in multimodal data fusion, etc. Target use cases include detection (greenhouse gas plume detection by volumetric measurement), subsurface detection (reduction of uncertainty ellipsoid (EOU), optimization of spacing, and detection of shallow subsurface pipeline integrity), and software integration applied to existing sensors for true autonomous operation (hardware-independent software).

[0013] The following paragraphs describe a distributed system 100 configured to implement a bidirectional time transfer protocol for synchronizing a plurality of sensor nodes 104a-104n. The distributed system 100 can enhance the synchronization accuracy of a high-precision timing protocol (PTP) based time synchronization network by utilizing a wireless over-the-air (OTA) calibration signal as a time focusing component. For example, the calibration signal can provide an additional reference clock that each of the plurality of sensor nodes 104a-104n can use to verify the time transfer accuracy of the time synchronization protocol under which the distributed system 100 is managed. In some embodiments, the time synchronization protocol may be any viable method of coordinating a plurality of independent clocks used to control and / or time-align the plurality of sensor nodes 104a-104n. The systems and methods described herein are intended to be time transfer protocol independent. To that end, some non-limiting embodiments of the time synchronization protocol can achieve sub-nanosecond accuracy using PTP (e.g., any viable version of IEEE 1588). In other words, in time synchronization protocols, the bidirectional exchange of PTP synchronization messages allows for precise adjustment of clock phase and offset, and link delay may be precisely known through accurate hardware timestamp and delay asymmetric calculations. Furthermore, OTA waveform calibration and synchronization methods may be used to wirelessly time-synchronize multiple nodes for distributed sensing systems. In some non-limiting embodiments, this synchronization may be performed sequentially per channel at coherent processing intervals (CPIs), achieving GPS-like wireless time synchronization fidelity for multiple nodes. This waveform synchronization may be achieved by (a) calculating the offset between nodes via RF, and (b) using a Wi-Fi peer-to-peer link to coordinate commands / controls using that offset.

[0014] In some embodiments, the distributed system 100 connects multiple sensor nodes 104a-104n in a noiseless zero-hop network using dedicated optical fiber time transfer channels and / or Ethernet time transfer channels. Furthermore, node excitation data for each of the multiple sensor nodes 104a-104n may be communicated via a separate communication channel such that the entire bandwidth of the dedicated time transfer channel is allocated to time transfer information. This time signal isolation creates a TWTT channel that communicates with the grandmaster without further signal data noise. This reduces the processing overhead and latency required to separate timing data from the nose in time transfer synchronization, thereby improving the accuracy and precision of the synchronization. The distributed system 100 utilizes a number of techniques that enable its aggregate to create a fully deterministic network for general-purpose data transfer and sub-picosecond accuracy time transfer. For example, the distributed system 100 may be configured in a Dynamic Adaptive Distribution (DyAD) processing architecture that can utilize a heterogeneous phased array of sensor nodes 104a-104n for multimodal sensor operations (e.g., adaptive mesh networking, multistatic simultaneous transmit / receive (STAR), time-based multisensor tasking, GPS jamming mitigation, GPS-independent positioning services, etc.). In the case of DyAD processing, the distributed sensor array system 100 may be configured as a scalable system of subarrays, each of which can function as a processor and / or timing distribution node for any number of lower sensor nodes 104a-104n. In some embodiments, the distributed system 100 facilitates the transmission and reception of radio frequency (RF) waveforms, but the distributed system 100 is not limited to operating with RF waveforms and may be configured to operate with other waveforms (e.g., sound waves, seismic waves, etc.).

[0015] Sensor node 104a may be configured to be only one of the following: (a) a transmit-only sensor node, in which case it can transmit waveforms but cannot receive them; (b) a receive-only sensor node, in which case it can receive waveforms but cannot transmit them; or (c) a transmit-and-receive sensor node, in which case it can transmit or receive waveforms. Unless otherwise stated, a sensor node can be both a transmit-and-receive sensor node. Each of sensor nodes 104a-104n may be configured to transmit an outgoing waveform (e.g., called a “probe signal”), all of which can be combined together to form a beam in a particular direction. Each of sensor nodes 104a-104n may receive a response to the probe signal (e.g., called a “data signal”), which may be “time-aligned” and combined by the distributed system 100 for further processing (e.g., by a third-party system) for one or more applications.

[0016] The distributed system 100 time-synchronizes the sensor nodes 104a-104n to time-align the transmitted probe signals or data signals received by the sensor nodes. In some embodiments, time-aligning the data signals involves adding at least one of the time offset, phase, or amplitude to the data signals so that the data signals of all sensor nodes 104a-104n have the same time offset, phase, and amplitude. The distributed system 100 can synchronize the sensor nodes 104a-104n in several ways. For example, each sensor node may have its own local clock (e.g., a crystal oscillator), which may be synchronized with a phase-locked loop, which may be synchronized with (a) an external clock signal wired to each receiver, or (b) a wireless external signal such as a GPS signal, an astrological signal (e.g., a quasar signal, a cosmic microwave background signal, or other signal from radio astronomy), a waveform from a television tower, an acoustic waveform, or a calibration signal from a transmitter node within the distributed system 100 (further details of which are described below). In another example, the local clock for each sensor node might consist of an atomic clock with a low-drift rubidium oscillator (which may not drift by more than a microsecond over a period of several days or months, for example), and the atomic clock for each sensor node may be synchronized and aligned at the factory before the sensor nodes are deployed.

[0017] In some embodiments, each of the sensor nodes 104a to 104n shares state information with the distributed system 100 (e.g., one or more other sensor nodes) so that any received signals or signals transmitted by the sensor node are calibrated and synchronized with each other to synchronize data acquisition across the distributed system 100. The state information may include the temperature of the sensor node in the environment; the position of the sensor node (determined by GPS, etc.); calibration metrics such as phase and amplitude offsets of RF components (or optical components in the case of an optical system); or a timestamp of the occurrence of an event, such as (a) the reception of a signal (e.g., a calibration signal, a GPS signal, or any other known waveform), or (b) the reception of a request for a local timestamp of the sensor node. In some embodiments, the distributed system 100 synchronizes each of the sensor nodes 104a to 104n with the reference node 106 of the distributed system 100 by calculating a time offset between the timestamp of the occurrence of the event at the reference node 106 of the distributed system 100 and the timestamp of the occurrence of the event at the corresponding sensor node. For example, if sensor nodes 104a to 104n are implemented using factory-calibrated atomic clocks, the sensor nodes of the distributed system 100 (e.g., the central processing node 108) send a request to each of the sensor nodes 104a to 104n, including the reference node 106 of the distributed system 100, to obtain the local timestamp of the corresponding sensor node and receive a response containing the local timestamp (e.g., the time the request was received at the corresponding sensor node). The distributed system 100 synchronizes the first sensor node 104a with the reference node 106 by calculating a time offset between the reference timestamp of the reference node 106 and the first timestamp of the first sensor node 104a. In some embodiments, the reference node 106 functions as a grandmaster node or master node in a PTP time transfer system, and the remaining sensor nodes are slave nodes synchronized to the clock of the reference node according to a time synchronization protocol.

[0018] In another example where the distributed system 100 is configured to synchronize the sensor nodes 104a - 104n using a calibration signal, the distributed system 100 synchronizes each of the sensor nodes 104a - 104n with the reference node 106 of the distributed system 100 by calculating the time offset between the time stamp of the reception of the calibration signal at the reference node 106 of the distributed system 100 and the time stamp of the reception of the calibration signal at the corresponding sensor node. For example, the distributed system 100 synchronizes the first sensor node 104a with the reference node 106 by calculating the time offset between the time stamp of the reception of the calibration signal at the reference node 106 and the first time stamp of the reception of the calibration signal at the first sensor node 104a.

[0019] When a probe signal is transmitted or a data signal is received by the sensor nodes 104a - 104n, the distributed system 100 (e.g., the central processing node 108) can generate time - aligned data signals for each of the sensor nodes 104a - 104n by adding the time offset corresponding to the probe signal or data signal of the sensor nodes 104a - 104n. Further details regarding the time synchronization of the sensor nodes 104a - 104n are described at least in reference to FIGS. 3 - 5 below.

[0020] After the data signals are time-aligned, the distributed system 100 combines the time-aligned data signals to generate a combined data signal with a coherent gain such that the power level of the combined signal can be a function of the individual time-aligned signals being combined. For example, the power level of the combined signal is the sum of the power levels of the individual time-aligned signals from different sensor nodes. In another example, the power level of the combined signal is greater than the power levels of the individual time-aligned signals from different sensor nodes. In some embodiments, the data signals are combined by adding together time-domain signals from different sensor nodes 104a - 104n such that the data signals are time-aligned and coherently added together. The combined signal may then be intelligently signal processed by the distributed system 100 or provided to a third-party system for one or more applications. One such application may include a monitoring application such as a radar system for determining one or more parameters (e.g., speed and distance of an aircraft) of an object within the environment of the distributed system 100. Another application may include the detection of radar pulses. Another application may include digital receive beamforming.

[0021] In some embodiments, one of the sensor nodes 104a - 104n is designated as a reference node 106 and its clock functions as a reference clock for synchronizing the clocks of the other sensor nodes 104a - 104n. In some embodiments, the central processing node 108 is one of the sensor nodes 104a - 104n configured to perform various types of processing such as calculation of time offsets, generation of time-aligned data signals, and combination of time-aligned data signals. In some embodiments, the central processing node 108 and the reference node 106 are the same sensor node.

[0022] In some embodiments, the sensor nodes 104a-104n can operate independently of each other and communicate wirelessly with other entities in the distributed system 100, so they do not need to be physically connected to each other. This makes the distributed system 100 not only easily scalable but also capable of being configured to operate at low frequencies for ultra-long-range and high-speed detection while keeping the size of the distributed system 100 to a minimum, which is a significant advantage over conventional phased array systems. Conventional phased array systems were very large or impractical to implement for low-frequency operation because the size of the antennas is inversely proportional to the transmit and receive frequencies, and the circuit boards housing such antennas are significantly large and difficult or impossible to manufacture. In the distributed system 100, the sensor nodes 104a-104n can be spaced apart from each other in units of distance λ / 2 (where λ is the wavelength of the signal). For example, if the frequency of the waveform transmitted by the sensor nodes 104a-104n is 50 MHz, corresponding to a wavelength of about 6 meters, the sensor nodes 104a-104n may be placed about 3 meters apart from each other. Sensor nodes 104a-104n, including the reference node 106 and the central processing node 108, may be located in the same location (e.g., within a specified number of wavelengths of the operating frequency) or may be located remotely (e.g., beyond a specified number of wavelengths of the operating frequency). For example, the first sensor node 104a and the second sensor node 104b may be located in the same location, while the reference node 106 may be located remotely. In another example, the first sensor node 104a and the second sensor node 104b may be located in the same location, while the third sensor node 104c may be located remotely. Regardless of how the sensor nodes 104a-104n are located, they can be synchronized as long as the location information of the sensor nodes 104a-104n, the reference node 106, or the central processing node 108 is available.For example, as described above, sensor nodes 104a-104n may have the ability to self-organize (e.g., share location information such as latitude, longitude, and altitude via state information) or self-calibrate (e.g., synchronize themselves with reference node 106). The distributed system 100 may have location information of reference node 106 and sensor nodes 104a-104n, which may be used when determining the time difference in the arrival of calibration signals at the sensor nodes relative to reference node 106, and which may be further used when determining the time offset between sensor nodes 104a-104n and reference node 106. Sensor nodes may self-calibrate on a scheduled basis using a factory-calibrated atomic clock, calibration signal, or other known waveform before transmitting a probe signal or before receiving a response to a probe signal.

[0023] Each distributed system 100 can be easily scaled up by adding sensor nodes or easily scaled down by removing them. Furthermore, since each sensor node 104a-104n can communicate directly with the reference node 106 or the central processing node 108, all sensor nodes 104a-104n are a single hop away from the reference node 106 or the central processing node 108, and any scaling of the distributed system 100 may not result in a decrease in time synchronization accuracy. In some embodiments, interferometric data may be obtained between sensor nodes by widely distributing the sensor nodes in space, and accurate angular accuracy may be obtained even at low frequencies.

[0024] Figure 1 shows a single cluster of sensor nodes 104a-104n, but the distributed system 100 may have several clusters, each cluster having some sensor nodes. Different clusters may have different or the same number of sensor nodes. In some embodiments, such a configuration allows for the detection of moving objects over very long distances and at high speeds; it enables a better angular resolution than that available with a single cluster. Also, some clusters remain completely passive, and since there is no active transmission, determining the location of the cluster becomes difficult to impossible. Yet another advantage of having multiple clusters is that one cluster may be at a much closer distance to the received signal, which may result in much less free-space path loss of the signal and thus a much stronger signal that can be shared between nodes. In some embodiments, clusters may be spread over hundreds of meters. Each cluster can generate a combined signal from the time-aligned signals of its constituent sensor nodes, and the combined signals from all clusters can be further combined to generate a master combined signal with coherent gain, such that the power level of the master combined signal is a function of the power levels of the constituent combined signals of different clusters. For example, the power level of the master combined signal is the sum of the power levels of the constituent combined signals of different clusters. In another example, the power level of the master coupling signal is greater than the power levels of any of the constituent coupling signals from different clusters.

[0025] Figure 2 is a block diagram of the sensor nodes of the distributed system of Figure 1, consistent with various embodiments. A sensor node (e.g., a first sensor node 104a) includes an antenna 202 that facilitates the radiation or reception of waveforms when connected to a transmitter or receiver (not shown). The antenna 202 may be configured to transmit or receive waveforms over a wide range of frequencies. The first sensor node 104a may include a clock 204 that generates a clock signal for use in synchronizing the operation of the first sensor node 104a (e.g., coordinating the order of operations). The clock 204 may be a crystal clock, an atomic clock, or another type of clock.

[0026] The first sensor nodes 104a to 104n may include a time synchronization component 208 that synchronizes the clock 204 of the first sensor node 104a in one of the methods described above. For example, the time synchronization component 208 synchronizes the clock 204 with an external signal, such as an external clock signal wired to the first sensor node 104a, or with a wireless external signal, such as a GPS signal or an astrological signal. In another example, the time synchronization component 208 synchronizes the clock 204 to the clock of the reference node 106 using a calibration signal from a transmitter node (further details of which are described with reference to at least Figures 3 to 5 below).

[0027] The first sensor node 104a includes a digital signal processor (DSP) 206 configured to perform various signal processing operations, including generating time-aligned signals, matching and filtering received calibration signals or data signals, setting the frequency range of the first sensor node 104a, and radar signal processing. In some non-limiting embodiments, the DSP 206 includes a field-programmable gate array (FPGA) that enables each sensor node 104a-104n to function as a reconfigurable master node capable of distributing a master timing signal to a plurality of slave nodes 104a-104n over a time transfer network. Each sensor node 104a-104n may be used as a reconfigurable time-synchronization interface capable of distributing a master time signal to a changing cluster or sensor nodes 104a-104n.

[0028] The first sensor node 104a includes an RF chain 210. In some embodiments, the RF chain 210 may be a cascade of electronic components and subunits, which may include amplifiers, filters, mixers, attenuators, and detectors. All of these components may be combined to serve a specific application (e.g., a radar system for detecting moving objects). One or more of the components (e.g., the DSP 206 and the time-synchronization component 208) may be implemented using an SDR. The SDR facilitates various functions. For example, the SDR can facilitate the acquisition of location information for sensor nodes 104a-104n, reference node 106, or central processing node 108 (e.g., using GPS). In another example, the SDR can facilitate the generation of time-aligned data signals.

[0029] It should be noted that one or more components of the first sensor node 104a may be communicatively coupled to another device of the distributed system 100 via a communication module to coordinate their operation. Some or all of the components of the first sensor node 104a may be combined as a single component. A single component may also be divided into sub-components, each sub-component performing separate method steps or multiple method steps of the single component. Any one or more of the components described herein may be implemented using hardware (e.g., a machine processor) or a combination of hardware and software. For example, any component described herein may have a processor configured to perform the operation described herein for that component.

[0030] Figure 3A shows an example of synchronizing sensor nodes 104a-104n using a calibration signal 304 from transmitter node 302 of distributed system 100. The calibration signal 304 may be of any frequency in a wide range. Figures 3-5 below show examples of TWTT synchronization using multiple modalities, including the use of a calibration signal from transmitter node 302, a local grandmaster clock, and / or a dedicated time distribution channel. Note that time synchronization is not limited to being performed using a calibration signal, and it can be performed in several ways as described above with reference to at least Figure 1. For example, sensor nodes 104a-104n may be time-synchronized using an external wireless signal such as the calibration signal 304, which is a known waveform, such as a GPS signal, an astrological signal, a seismic signal, an acoustic signal, a signal transmitted from a transmitter (e.g., a signal from a television tower), or a signal transmitted from the transmitter node of distributed system 100. In another example, time synchronization may be achieved by using a factory-calibrated atomic clock within sensor nodes 104a-104n. Furthermore, while Figures 3 to 5 illustrate time synchronization with reference to data signals received by sensor nodes 104a to 104n, it should be noted that the concept of time synchronization is not limited to data signals received by sensor nodes, but is also applicable to probe signals transmitted by sensor nodes.

[0031] Figure 3A is a block diagram of the time synchronization of sensor nodes in the distributed system of Figure 1, consistent with various embodiments. Transmitter node 302 may be located in the same location as sensor nodes 104a-104n or it may be located remotely. In some embodiments, transmitter node 302 is considered to be located in the same location as sensor nodes 104a-104n if transmitter node 302 is within a specified proximity to sensor nodes 104a-104n (e.g., a specified number of wavelengths of the calibration signal 304). For example, if the transmission frequency of transmitter node 302 is 144 MHz, transmitter node 302 is considered to be located in the same location as sensor nodes 104a-104n if it is within a threshold distance (e.g., 20-50 meters) of any of the sensor nodes 104a-104n. Transmitter node 302 is considered to be located remotely if it is beyond a specified proximity to sensor nodes 104a-104n (e.g., beyond 50 m at a frequency of 144 MHz). In some embodiments, if the transmitter is very powerful (e.g., hundreds or thousands of watts per transmit power amplifier with multiple transmit antennas creating a transmit phased array, and the transmit frequency is 50 MHz), the transmitter node 302 can even be positioned beyond the horizon. Furthermore, the transmitter node 302 may also be configured to be moving, in motion, or running. In some embodiments, by positioning and moving the transmitter node 302 remotely from the sensor node, a "cannot be detected" sensor system may be established (e.g., the transmitter node 302 is not located in the same place as the receiver sensor node, so an adversary cannot use the transmitter signal to geographically locate the receiver sensor node).

[0032] Regardless of whether the transmitter node 302 is located in the same location or remotely, the transmitter node 302 is located in a known location relative to the sensor nodes 104a-104n, and the calibration signal 304 may be "seen" (e.g., the calibration signal 304 is above the noise) or received by the sensor nodes 104a-104n without requiring signal processing. For example, the distributed system 100 can know the location information (e.g., latitude and longitude information) of the transmitter node 302. Such a configuration provides the flexibility to place the transmitter node 302 in any of the various locations and also eliminates the need for the sensor nodes 104a-104n to be in line of sight to each other.

[0033] Each of the sensor nodes 104a to 104n, including the reference node 106, receives a calibration signal 304 and determines the timestamp of receipt of the calibration signal 304. Based on the timestamps of the sensor nodes 104a to 104n and the timestamp of the reference node 106, the distributed system 100 calculates the time offset of the sensor nodes 104a to 104n to synchronize them with respect to the reference node 106. Further details on how the calibration signal 304 from the transmitter node 302 is used to synchronize the sensor nodes 104a to 104n with respect to the reference node 106 in the distributed system 100 are described in more detail in Figures 5A to 5C below.

[0034] Figure 3B is a block diagram of one embodiment of a noiseless time distribution network 301 used to perform time synchronization and / or general communication operations. The noiseless time distribution network 301 may refer to a communication network that includes at least one dedicated wired connection between the components that are thereby synchronized. This wired connection is dedicated to timing signal information and may be shielded from external noise or interference. Furthermore, the noiseless wired connection may be augmented by an additional wireless transmit calibration signal that acts as a time focusing element to enhance synchronization fidelity. In some embodiments, the noiseless time distribution network 301 comprises two main components: a master array node 303 and a transmitter node 302. The master array node 303 may be a plurality of sensor nodes 104a-104n configured within a zero-hop master-slave PTP network. The implementation of a dedicated TWTT channel 318 to create a scalable zero-hop network ensures that the load on the network and the number of hops in the topology do not degrade the time synchronization resolution. In some embodiments, a primary grand master clock 332 serves as the absolute time source for the primary master node 106a. Next, the master node 106a distributes the time signal data to the time distribution interface 314 via a dedicated TWTT channel 318. In some embodiments, the dedicated TWTT channel 318 is a bidirectional communication link for the time signal data. The system 100 can use high-density wavelength division multiplexing to enable the dedicated TWTT channel 318 to send and receive multiple simultaneous timing signals 308 (e.g., NTP, 1PPS, 10MHz) over a single TWTT channel. In some embodiments, the time signal data may be passed from the primary master node 106a to a time synchronization interface that distributes the time signal data to multiple local slave nodes 316a using the IEEE 1588-2019 time transfer protocol. Each of the multiple local slave nodes 316a may include multiple antenna elements capable of receiving the OTA time calibration waveform 304 broadcast by the transmitter node 302.In some non-limiting embodiments, the distributed system 100 may include multiple sensor nodes 104a-104n that utilize multiple transmitter nodes 302 and / or transmit OTA time calibration waveforms 304. For example, the use of multiple transmitter nodes 302 distributed across a region can enable the system to achieve higher time synchronization fidelity and / or introduce operational redundancy. The OTA time calibration waveforms 304 are generated after the processor node 108a generates a master timing signal 328 that is distributed to the relevant control components of the noiseless time distribution network 301. The master timing signal may include slave node listen window scheduling commands, the OTA time calibration waveforms 304, and / or calculated time offsets between nodes. In some embodiments, the processor node 108n and the secondary master node 106n are included in the transmitter node 302. This feedback loop enables the noiseless time distribution network 301 to continuously update and improve time synchronization fidelity. In some embodiments, the master node 106a synchronizes a master timing signal 328 transmitted via a dedicated timing data channel 318 with a plurality of slave nodes 316, and then the master processor node 108a combines the data. The combined synchronization data signals from the plurality of slave nodes 316 generate a composite signal having a power level greater than any of the power levels of the sensor nodes 104a to 104n.

[0035] Continuing to refer to Figure 3B, embodiments of the distributed system may include multiple remote slave nodes located up to several hundred kilometers away from the primary master node, maintaining even higher timing accuracy and precision (e.g., picosecond time resolution). In some embodiments, fiber optic cables are inputs to the time synchronization interface 314, with outputs of 1 PPS / 10 MHz signals and PTP Ethernet. This architecture allows multiple remote slave nodes 316b to be located 1 m to 100+ km from the master node.

[0036] In some embodiments, multiple sensor nodes grouped into a subarray may be decomposed into a single node weight vector for signal processing. Thus, node excitation data provided by a single node 104a may represent multiple slave nodes 316. In some embodiments, the noiseless time distribution network 301 includes a distributed, redundant, and calibrated atomic clock, a Global Navigation Satellite System (GNSS) time receiver, and an optical fiber TWTT channel 318, the references of which are scattered over up to several hundred kilometers. In this way, the distributed system 100 can acquire and maintain fidelity of the backbone time transfer components (e.g., a secure master reference node 106a, a primary grandmaster clock 332, and a master processor node 108a). This arrangement allows the noiseless time distribution network 301 to distribute the available time references from multiple sensor nodes 104a-104n to locations that encounter faults or GNSS interference. In some embodiments, each of the multiple slave nodes 316 represents a cluster of sensor nodes synchronized with a secondary master node 106n and / or a grandmaster clock. Each of the slave node clusters 316 may be connected to a secondary master node 106n via a corresponding secondary timing channel, thereby synchronizing the secondary master node 106n with the primary master node 106a. In some embodiments, the distributed system 100 can implement a scalable chain of master-slave node clusters to extend its operational capabilities. For example, a processor node 108a may employ multiple lower-level sensor node clusters to perform passive radar operations. Each of the lower-level sensor node clusters may synchronize with its own lower-level master node and / or lower-level master clock. The lower-level master clock may synchronize with the grandmaster clock 332 of the master array node 303. This architecture may allow the processor node 108 to implement a multi-hop network in which the number of hops is calculated to achieve the desired system-wide time synchronization fidelity.The primary master node 106a and slave nodes 316 can communicate via a bidirectional stateless connection. Furthermore, the master array node 303 can implement boundary clocks and transparent clocks in the time synchronization interface 314, thereby enabling multiple timing network architectures. Figure 3C is a block diagram of one embodiment of TWTT synchronization operation in which the master node 106 connects multiple slave nodes 316 using multiple wired TWTT channels 320. In some embodiments, time focusing techniques for multi-node networks significantly reduce time errors by adjusting "one-to-many" negotiations rather than "one-to-one" negotiations. One-to-many time focusing techniques provide more data to average out errors and improve the accuracy of the time difference of arrival (TDOA). Specifically, by measuring the timing offset and / or error for each of the multiple slave nodes over multiple synchronization cycles and then averaging them, the processor node 108 can better understand and offset the true time offsets for the multiple slave nodes 104a-104n relative to the master node 106. For example, the master node 106 can perform longitudinal averaging of time offsets to determine the true time offset across multiple synchronization cycles. Similarly, the master node 106 can calculate the time offset for each of the multiple slave nodes 104a to 104n and average the time offsets to determine the true time offset for the distributed system 100. Furthermore, the master node 106 can perform longitudinal averaging of time offsets to determine the true time offset across multiple synchronization cycles. In another embodiment, the master node 106 performs spatial averaging of time offsets to determine the true time offset across the multiple slave nodes 104a to 104n at any given time.

[0037] In some embodiments, true offset acquisition is managed by machine learning algorithms that analyze the performance of the distributed system 100 to identify and address sources of network and / or processing latency. Thus, the distributed system adaptively responds to temporal, spatial, and computational defects that degrade synchronization accuracy. In some embodiments, a master node 106 transmits a master timing signal 328 to a plurality of slave nodes 104a-104n via a wired TWTT channel 320, and the plurality of slave nodes 316 transmit responses via a wireless TWTT channel 322. Thus, the system 100 is designed to identify and use the most advantageous means of time-transfer messaging. For example, the master node 106 can transmit a timestamped message instructing each of the plurality of slave nodes 316 to transmit a slave timing signal at a known future time. When a slave timing signal is transmitted at a known future time and received by the master node 106, the difference between the known future time and the time of reception by the master node 106 is used to calculate a node-specific time offset that correlates with the distance between the master node 106 and the corresponding slave node from the multiple slave nodes 316.

[0038] In some embodiments (e.g., Figures 3B and 3C), data collected or transmitted by each of the multiple sensor nodes is sent to the processor node 108 via the data transfer channel 330. Figure 3C depicts a noiseless time distribution network 301 in a zero-hop network configuration where there is no router between the master node 106 and the slave nodes 316. This configuration facilitates any node 106n calibrating the master array node 303 based on the true time delay between multiple antenna nodes (e.g., antenna data elements 306). Furthermore, the true time delay may be a node-specific time offset for each of the multiple slave nodes 316 on the noiseless time distribution network 301. This node-specific time offset may be calculated adaptively to compensate for movement or changes in state of sensor nodes. For example, antenna nodes 104a-104n may be communicably coupled via at least one of a wired connection 320 or a wireless connection 322. In some embodiments, each of the multiple sensor nodes 104a-104n may be communicatively coupled and synchronized with one another to enable a phase-coherent channel for beamforming operation. Furthermore, a processor 206 per sensor node 104a (Figure 2) may be synchronized via 1588PTPv2. Data generated in connection with commands / controls may be synchronized within two-digit nanosecond precision. Distributed systems may be advantageously used on a network of small, low-power nodes to create a communication network with low-probability-of-detection / low-probability-of-interception (LPD / LPI) communications, and also promote resilience in competitive environments and enable "stand-in" solutions.

[0039] Exemplary flowchart

[0040] This specification includes illustrative flowcharts of the processing operations of methods that enable the various features and functions of the system described in detail above. The processing operations of each method presented below are intended to be illustrative and non-limiting. In some embodiments, for example, a method may be achieved by one or more further operations not described and / or without one or more of the operations described. Furthermore, the order in which the processing operations of a method are shown (and described below) is not limiting.

[0041] In some embodiments, the method may be carried out in one or more processing devices (e.g., digital processors, analog processors, digital circuits designed to process information, analog circuits designed to process information, state machines, and / or other mechanisms for electronically processing information). The processing device may include one or more devices that perform some or all of the operations of the method in response to instructions electronically stored in an electronic storage medium. The processing device may include one or more devices configured via hardware, firmware, and / or software specifically designed to perform one or more of the operations of the method.

[0042] Figure 4A shows a flowchart of method 400 for synchronizing sensor nodes in a distributed system, consistent with various embodiments. Method 400 is an example of synchronizing sensor nodes, in which sensor nodes 104a-104n synchronize with a reference node in the distributed system using calibration signals from a transmitter node. In some embodiments, method 400 may be implemented in a sensor node, reference node, or central processing node of the distributed system 100. In operation 402, calibration signals from the transmitter node are received by each of the sensor nodes (e.g., receiving sensor nodes), including the reference node. For example, the first sensor node 104a, the second sensor node 104b, and the reference node 106 of the distributed system receive calibration signals 304 from the transmitter node 302 (e.g., as described with reference to at least Figure 3 above).

[0043] In operation 404, the timestamp of the reception of the calibration signal is determined by each of the sensor nodes 104a to 104n (e.g., the receiving sensor nodes) and the reference node. For example, the first sensor node 104a determines the first timestamp of the reception of the calibration signal 304 (e.g., based on the clock of the first sensor node 104a), the second sensor node 104b determines the second timestamp of the reception of the calibration signal 304, and the reference node 106 determines the reference timestamp of the reception of the calibration signal 304.

[0044] In some embodiments, the calibration signal 304 may be a transmission pulse of a specified duration (e.g., 10 to 1,000 microseconds in length), in which case the sensor node can compress the received timestamp into a single point in time. The signal may be compressed into a single point in time in several ways. For example, the first sensor nodes 104a to 104n may compress the calibration signal into a single point in time using a matching filter (e.g., a matching filter algorithm).

[0045] In operation 406, the time offset of the sensor nodes relative to the reference node is calculated based on the timestamps of reception of the calibration signal at the corresponding sensor nodes 104a-104n (e.g., the receiving sensor node) and the timestamp of reception of the calibration signal at the reference node. In some embodiments, the time offset may be calculated by the central processing node 108. The sensor nodes 104a-104n and the reference node 106 can transmit their corresponding timestamps to the central processing node 108, which can then calculate the timestamps. For example, suppose the reference timestamp of reception of the calibration signal 304 recorded by the reference node 106 is "1.00" nanoseconds, the first timestamp of reception of the calibration signal 304 recorded by the first sensor node 104a is "1.05" nanoseconds, and the second timestamp of reception of the calibration signal 304 recorded by the second sensor node 104b is "0.98" nanoseconds. The reference node 106, the first sensor node 104a, and the second sensor node 104b send their corresponding timestamps to the central processing node 108. The central processing node 108 calculates the first time offset of the first sensor node 104a by subtracting the reference timestamp ("1.00") from the first timestamp (e.g., "1.05") to obtain the first time offset (e.g., "1.05" - "1.00" = "0.05" nanoseconds). Similarly, the central processing node 108 calculates the second time offset of the second sensor node 104b by subtracting the reference timestamp ("1.00") from the second timestamp (e.g., "0.98") to obtain the second time offset (e.g., "0.98" - "1.00" = "-0.02" nanoseconds). In some embodiments, the central processing node 108 can store these time offsets in a storage device (not shown), and as a result, when it receives data signals from the first and second sensor nodes in the future, it may synchronize the two sensor nodes by adding the corresponding time offsets to the data signals to generate time-aligned data signals.

[0046] In some embodiments, the central processing node 108 may also consider the arrival time differences of the calibration signal 304 from the transmitter node 302 to different sensor nodes 104a-104n in order to calculate the time offset. In some embodiments, the arrival time difference represents the difference between the time the calibration signal arrives at a particular sensor node and the time the calibration signal arrives at the reference node 106. If all sensor nodes 104a-104n are located in the same place (e.g., within a specified number of wavelengths of the calibration signal 304), the arrival time differences at the speed of light can be ignored, and therefore the arrival time differences can also be ignored, and thus the calculation of arrival time differences may not be necessary, and the calculation of the time offset based on timestamps may be accurate. However, if sensor nodes 104a-104n are not located in the same place (for example, across a specified number of wavelengths of the calibration signal 304), the arrival time difference of the calibration signal 304 from transmitter node 302 to sensor nodes 104a-104n may be calculated so that the sum of the time offset, arrival time difference, and timestamp is the same for all sensor nodes 104a-104n. The arrival time difference may be calculated based on the speed of light and known location information of transmitter node 302 or sensor nodes 104a-104n. As an example, if two nodes are located in exactly the same place but the arrival time difference of the calibration signals is 1 microsecond, the time offset is adjusted by only 1 microsecond. On the other hand, if there is a sensor node located 100 meters away in the direction from which the calibration / reference signal is moving, this is equivalent to "333" nanoseconds at the speed of light. Therefore, if the time difference of the signal reaching the further node is "1,333" nanoseconds after the first / reference node, the time offset is only 1 microsecond to offset the distance offset.

[0047] In operation 408, sensor nodes 104a to 104n synchronize based on at least a time offset to generate a time-aligned data signal for each of the sensor nodes 104a to 104n. In some embodiments, the time-aligned signal is a data signal aligned in time (and phase or amplitude) with a data signal received by another sensor node (e.g., reference node 106). The time-aligned data signal may be generated in various ways. Figures 5A to 5C are block diagrams illustrating the generation of time-aligned data signals for sensor nodes in a distributed system, consistent with various embodiments.

[0048] Figure 4B shows a flowchart of routine 410 for generating a master timing signal from the grandmaster clock 332 of the time transfer network that synchronizes the master array node 303 (Figure 3B). The routine may include establishing a zero-hop network architecture between a plurality of sensor nodes 104a-104n via processor node 108a, each of the plurality of sensor nodes 104a-104n having a dedicated TWTT channel 318 used to communicate with the master node 106a and other nodes in the distributed system 100 (412). The routine may also include designating the master node 106a and a plurality of slave nodes 316 via processor node 108a, where the master node 106a communicates with the dedicated TWTT channel 318 for each of the plurality of slave nodes 104a-104n to form the master array node 303 in the noiseless timing distribution network 301 (414).

[0049] In some embodiments, the master node 106a performs diagnostic operations to evaluate the state and health of the time synchronization accuracy between the master node 106a and the multiple slave nodes 316, the time synchronization fidelity of the grandmaster clock 332 to both the master node and the multiple slave nodes, the time offset and / or time deviation, and the achieved frequency deviation (Figure 3B). The master node 106a can update the time synchronization schedule during adaptive improvement. For example, adaptive improvement may include generating a synchronization window protocol via the primary master node 106a and communicating timing signal data with the multiple slave nodes 104a-104n according to the synchronization window protocol (416). The synchronization window protocol generates precise instructions for each of the multiple slave nodes 104a-104n that instruct when to begin listening for timing signal data used to synchronize the time synchronization protocol implementation. The distributed system 100 can reduce processing overhead and improve time synchronization fidelity by modifying the synchronization window protocol. For example, a slave node 316 can constantly listen to timing signal data, thus consuming a considerable amount of system resources. Alternatively, a slave node 316 can listen to timing signal data during a scheduled window according to a synchronization window protocol. In some embodiments, a slave node 316 adaptively determines when to listen to timing signal data according to a synchronization window protocol. For example, a distributed system may recognize an abnormal amount of latency and determine that the listening window should be modified to adjust a damaged TWTT channel 318. A slave node 316 can ignore unwanted data captured during a listening window according to a synchronization window protocol, thereby reducing processing and / or transmission overhead.

[0050] In some embodiments, the master node 106 monitors the primary clock drift for the grandmaster clock 332 and the secondary clock drift for the corresponding slave clocks (e.g., clock 204 in Figure 2) contained in each of the multiple slave nodes 316. The master node 106 can update the maser timing signals and modify the synchronization window protocol based on the primary clock drift. Furthermore, the master node can resynchronize the slave nodes 316 if the secondary clock drift exceeds a desired threshold. Thus, the distributed system adapts to changing clock times and maintains sub-picosecond time synchronization accuracy.

[0051] In the first example 500 shown in Figure 5A, all sensor nodes 104a-104n (e.g., sensor nodes with receiving capabilities), such as the first sensor node 104a, and the reference node 106, transmit their timestamps of receiving the calibration signal to the central processing node 108. For example, the first sensor node 104a transmits a first timestamp (e.g., "1.05" nanoseconds) to the central processing node 108, and the reference node 106 transmits a reference timestamp (e.g., "1.00" nanoseconds) to the central processing node 108. Note that in the examples in Figures 5A-5C, the reference node 106 and the central processing node 108 are shown as separate nodes. However, in other embodiments, the reference node 106 and the central processing node 108 may be the same sensor node. After receiving a timestamp, the central processing node 108 calculates a first time offset for the first sensor node 104a as the difference between the first timestamp and the reference timestamp (e.g., "1.05" - "1.00" = "0.05" nanoseconds). Similarly, the central processing node 108 calculates a second time offset for the second sensor node 104b (not shown in Figure 5A) as the difference between the second timestamp and the reference timestamp (e.g., "0.98" - "1.00" = "-0.02" nanoseconds). The central processing node 108 may further store the first and second time offsets in a memory device associated with the central processing node 108 (not shown). When the sensor nodes and reference nodes receive a data signal (e.g., a response to a probe signal transmitted by a sensor node and reflected by an object such as an aircraft), the sensor nodes and reference nodes transmit the received data signal to the central processing node 108. For example, the first sensor node 104a and the reference node 106 each transmit the received first data signal and reference data signal to the central processing node 108. The central processing node 108 can then retrieve the first time offset from the storage device and add it to the first data signal to generate the first time-aligned data signal of the first sensor node 104a.Similarly, the central processing node 108 can generate a second time-aligned data signal from the second sensor node 104b by adding a second time offset to the second data signal from the second sensor node 104b.

[0052] In some embodiments, generating time-aligned data signals may involve equalizing data signals received by sensor nodes. Equalization can be the process of adjusting at least one of the phase, amplitude, and time offset of the data signal so that the received waveforms at all sensor nodes have the same amplitude, phase, and time offset characteristics. For example, equalizing a first data signal received by a first sensor node may involve adjusting at least one of the phase, time, or amplitude so that the first data signal aligns in time, phase, or amplitude with a data signal received by another node (e.g., a reference node). In some embodiments, only one of time offset, phase adjustment, or amplitude adjustment may be applied to equalize the received data signals. Differences in amplitude, phase, and time delay between signals introduce errors in beamforming and coupling of signals, leading to a degradation of coherent "gain." By equalizing the received data signals, errors in gain and beamforming patterns are minimized. Equalization may be performed via a finite impulse response (FIR) filter or an infinite impulse response (IIR) filter. In some embodiments, equalization is performed via an FIR. In some embodiments, the same FIR filter is used across multiple data signals, thereby minimizing the computational resources consumed when equalizing data signals, unlike conventional systems where an FIR filter may be used for each received signal, which can be computationally intensive.

[0053] Therefore, the central processing node 108 can generate time-aligned data signals by equalizing the received data signals, as shown in the first example 500 in Figure 5A.

[0054] In the second example 510 of Figure 5B, each sensor node can generate its own time-aligned data signal based on a time offset calculated by the central processing node 108. For example, the first sensor node 104a and the reference node 106 each send a first timestamp and a reference timestamp to the central processing node 108. The central processing node 108 calculates a first time offset for the first sensor node 104a based on the first timestamp and reference timestamp (for example, as described above with reference to Figure 5A) and sends the first time offset to the first sensor node 104a. When a sensor node receives a data signal (for example, a response to a probe signal transmitted by a sensor node, where the response is reflected from an object such as an aircraft), the sensor node generates a time-aligned signal based on its received time offset. For example, when the first sensor node 104a receives a first data signal, the first sensor node 104a can add the received first time offset to the first data signal to generate the first time-aligned data signal of the first sensor node 104a. The reference node 106 also receives the data signal. In some embodiments, the first sensor node 104a generates the first time-aligned data signal by adding a "true time delay" to the first data signal using its DSP 206.

[0055] In the third example 520 in Figure 5C, when a data signal is received by a sensor node, sensor nodes 104a to 104n synchronize their local clocks based on the received time offset so that the data signals of sensor nodes 104a to 104n are time-aligned. For example, the first sensor node 104a and the reference node 106 each send a first timestamp and a reference timestamp to the central processing node 108. The central processing node 108 calculates a first time offset for the first sensor node 104a based on the first timestamp and reference timestamp (for example, as described above with reference to Figure 5A) and sends the first time offset to the first sensor node 104a. The first sensor node 104a synchronizes its local clock based on the received first time offset so that its clock is synchronized with the clock of the reference node 106. When a sensor node receives a data signal (for example, a response to a probe signal transmitted by a sensor node, where the response is reflected from an object such as an aircraft), the timestamps (of the reception of the data signal) recorded on sensor nodes 104a to 104n are the same as those on reference node 106 because their clocks are synchronized with reference node 106, and therefore the data signals of sensor nodes 104a to 104n are time-aligned. For example, when the first sensor node 104a and reference node 106 receive a data signal, the timestamp (of the reception of the data signal) recorded on the first sensor node 104a is the same as the timestamp (of the reception of the data signal) recorded on reference node 106 because the clock of the first sensor node 104a is synchronized with reference node 106, and therefore the data signal of the first sensor node 104a is time-aligned with the data signal of reference node 106.

[0056] The preceding paragraphs describe operations performed with respect to a single sensor node (e.g., the first sensor node 104a), but operations described with reference to operations 402-408 and Figures 5A-5C may be performed on all sensor nodes 104a-104n in the distributed system 100 that are capable of receiving waveforms. Furthermore, the above paragraphs describe operations performed by a single sensor node, such as the central processing node 108 (e.g., time synchronization), but operations may be performed by another sensor node, such as the reference node 106, or by two or more sensor nodes. For example, if processing is distributed, any number of sensor nodes can perform time synchronization or time alignment of data signals. Furthermore, time synchronization (e.g., operations 402-406 for calculating time offsets) may be performed on a schedule, before transmitting probe signals or before receiving data signals.

[0057] Figure 6 shows a timing sequence diagram for synchronization between the master array node 303 and the transmitter node 302. Synchronization begins with operations 601 and 602, when the primary master node 106a and the secondary master node 106b are powered on. Synchronization operations 603 and 604 are mirrored by operations 608 and 609, which enable the primary master node 106a and the secondary master node 106b to obtain time signals from the ground master clock 332. In operation 605, the master processor node 108a uses the ground master time signal to synchronize the time distribution interface 314. Operations 606, 607, and 608 enable the components of the master array node 303 and the transmitter node 302 to synchronize internally before establishing an inter-component communication channel in operation 611. Furthermore, operations 603-610 may be repeated indefinitely until the system 100 is powered off. Operation 612 initializes a time focusing routine used to further improve the time synchronization fidelity of the distributed system 100 using a calibration signal from transmitter node 302. Operations 613, 614, 615, 616, 617, 618, and 619 are used to synchronize multiple slave nodes 316 and WRS314 with the master processor node 108a. Similarly, operations 620, 621, 622, 623, and 624 are used to synchronize any node 104a with the secondary processor node 108n. In operation 625, the secondary processor node 108b transmits a calibration signal 304 before transitioning to a standby state in operation 626. The standby operation 627 may persist between operations 628 and 629 until a command is received from an external control system 650 (e.g., the Internet, a user device, etc.). Operations 630, 631, and 632 allow the master processor node 108a to be recalibrated against the secondary processor node 108b when a start command is received. Operations 633, 634, and 635 allow the distributed system 100 to continue its operational phase and periodically report system data to the external control system 650.Operation 636 may include a command to transition system 100 to the listening loop 638 via operation 637. Operations 639, 640, 641, 642, 643, and 644 describe the process for resynchronizing the components of master array node 303 to master processor node 108a, resynchronizing the components of transmitter node 302 to secondary processor node 108n, and resynchronizing master array node 303 to transmitter node 302. Operations 645, 646, 647, 648, and 649 are routines for improving system operation using the recalibrated system time as feedback.

[0058] In some embodiments, the aggregation of time-aligned data signals from sensor nodes of a distributed system may be performed using a central processing node 108 of the distributed system 100. Time-aligned data signals from sensor nodes 104a to 104n are acquired. In some embodiments, time-aligned data signals are generated as described with reference to at least Figures 4 and 5A to 5C above. For example, the central processing node 108 can generate time-aligned signals from sensor nodes 104a to 104n based on the corresponding time offsets of sensor nodes 104a to 104n, or it can acquire time-aligned signals from sensor nodes 104a to 104n.

[0059] Time-aligned signals may be combined (e.g., added) to produce a composite signal. The composite signal may have coherent gain such that the power level of the composite signal can be a function of the individual time-aligned signals being combined. For example, the power level of the composite signal is the sum of the power levels of the individual time-aligned signals from different sensor nodes. In another example, the power level of the composite signal is greater than the power levels of the individual time-aligned signals from different sensor nodes. In some embodiments, the combination of time-aligned data signals is performed by a central processing node 108. In some embodiments, the sensor nodes perform the combination of time-aligned signals (e.g., in a daisy-chain format) instead of all sensor nodes 104a-104n sending their time-aligned signals to the central processing node 108 to combine all of them. For example, a "binary" tree algorithm may be used for synthesis, where the first sensor node 104a synthesizes a time-aligned signal with the second sensor node 104b to generate a first combined signal, the third sensor node 104c synthesizes with the fourth sensor nodes 104a to 104n to generate a second combined signal, then the second sensor node 104b shares the first combined signal with the fourth sensor nodes 104a to 104n, the fourth sensor nodes 104a to 104n synthesize the first combined signal with the second combined signal to generate a third combined signal, and so on.

[0060] In some embodiments, the combined or synthesized signals may then be processed for a desired application. For example, the synthesized signal may be used in radar applications to measure one or more parameters related to the object (e.g., aircraft) (e.g., distance or speed of the aircraft) from signals emitted by an object. Processing of the combined signal may be performed by the distributed system 100 or by a third-party system, in which case the combined signal is provided as input to the third-party system.

[0061] Figure 7A shows a block diagram of a multistatic passive radar network used for blind channel estimation of the position, velocity, and orientation of multiple targets 704. In this passive radar network, multiple sensor nodes 104a-104n listen to ambient electromagnetic signals 708 to determine the relevant characteristics of the targets 704. The distributed system can use a blind channel estimation method for passive sensing by an unknown reference signal or transmitter signal 706 in a coherent distributed radar network. In some embodiments, the distributed system 100 implements a supersampling system that generates multiple digital snapshots of node excitation data for each of the multiple SDR sensor nodes 104a-104n. Since the sensor nodes 104a-104n use SDR, it is obvious that any snapshot of the array data can be digitally reconstructed. In some embodiments, the distributed system 100 can synthesize digital snapshots to overcome the current time synchronization limitations of the passive radar system by performing supersampling with picosecond time synchronization. The distributed system 100 may be configured as a multi-static radar system that uses the aforementioned time-focusing technique to reduce the time error associated with blind channel estimation for passive multi-target detection. For example, the distributed system 100 can use open-design, low-cost COTS SDRs, time-synchronization protocols, and time-synchronization waveforms and algorithms. The distributed system can also perform longer-range detection. The resilience of these systems largely depends on their ability to evade detection by adversaries. In contrast to active systems that emit large electromagnetic pulses, passive systems have near-zero electromagnetic signatures and are therefore extremely difficult for adversaries to detect, thus more favoring deployment in competitive environments.

[0062] In scenarios involving some limited knowledge of the reference signal, during active bistatic operation, the distributed system 100 can leverage a priori knowledge of the characteristics of transmitter 702 to perform radar processing without requiring a direct path signal from transmitter 702. For example, the distributed system 100 can improve passive radar solutions by leveraging a priori knowledge of non-cooperative transmitter 702 whenever possible (e.g., acquired via ELINT). Furthermore, system 100 can operate as a passive architecture when possible, if any number of sensor nodes transition between active operation and passive detection to respond to threats and / or changing environmental conditions.

[0063] As shown in Figure 7B, passive systems (e.g., 104a-104n) must operate with limited or no knowledge of transmitter 702 and its channel characteristics. This can significantly complicate efforts to correlate sensor waveforms to accurately detect and track targets 704. Signal extraction requires a very clean “reference signal” describing multiple unreflected transmitter waveforms 706. If the transmitter signal 706 is unknown, it must be measured, which typically requires a line-of-sight and directional antenna to the transmitter. In addition, processing gain is compromised because the transmitted waveform 706 is not optimized for radar. The signal detection problem is exacerbated in environments with a lot of clutter and / or multiple uncoordinated transmitters. These problems make the correlation of signals acquired from multiple receivers computationally difficult to handle. In some embodiments, the distributed system 100 uses a method in which a passive distributed radar system can detect multiple targets 704 with a high detection probability due to the location of an unknown transmitter 702 and unknown channel characteristics. For example, given the location of an unknown transmitter 702, the number of targets 704 can be detected as the number of available receiving nodes 104a-104n using a blind channel estimation method. As long as the passive receiving nodes 104a-104n are sufficiently networked so that the signal data received at Rx1,y1 and the signals received at Rx2,y2 can be shared with each other with sufficient temporal resolution, multiple representative signals 710 (e.g., channels h1' and h2') can be sufficiently estimated to resolve the accurate detection of targets 704. In some embodiments, time synchronization and time focusing techniques allow the time error to approach zero, thus enabling the establishment of a tactically relevant passive distributed radar system. Furthermore, the system can implement machine learning algorithms to improve the MIMO radar system and demonstrate accurate time-synchronized blind channel estimation for operationally relevant conditions.

[0064] Referring to Figures 3B and 7B, some embodiments of the passive signaler protocol may include each of the multiple sensor nodes 104a-104n sharing state information of the corresponding sensor node 104b with the sensor array system (e.g., distributed system 100). The passive signaler protocol may further include synchronizing the multiple sensor nodes 104a-104n based on the state information of the multiple sensor nodes 104a-104n, which is used to synchronize data signals received or transmitted by the multiple sensor nodes 104a-104n. The passive signaler protocol may further include generating a corresponding master timing signal 328 for each of the multiple slave nodes 316 (Figure 3B) via the primary master node 106a. The passive signaler protocol may further include communicating the corresponding master timing signal (master timing signal 328) for each of the multiple slave nodes 316 via the primary master node 106a through a corresponding timing data channel (e.g., a dedicated TWTT channel 318). In some embodiments, the primary master node 106a resynchronizes multiple slave nodes 316 to maintain picosecond time resolution. Furthermore, multiple slave nodes 316 and / or the processor node 108 can perform adaptive angle of arrival adjustments on passively received signals to determine the position, azimuth, and velocity of at least one target 704. In some embodiments, the synchronous operation cancels out the target's velocity and gravitational field data when operating on a relativistic scale.

[0065] In another example where the distributed system 100 is configured to synchronize sensor nodes 104a to 104n using calibration signals, the distributed system 100 synchronizes each of the sensor nodes 104a to 104n with the reference node 106 of the distributed system 100 by calculating a time offset between the timestamp of reception of the calibration signal at the reference node 106 of the distributed system 100 and the timestamp of reception of the calibration signal at the corresponding sensor node, as described with reference to at least Figures 3 to 5.

[0066] In some embodiments, after synchronizing the sensor nodes 104a to 104n, the time-matched signals are combined (e.g., added) to generate a composite signal, as described with reference to at least Figure 6 above.

[0067] Figure 8 is a block diagram of radar system 800 implemented using the distributed system of Figure 1, consistent with various embodiments. Radar system 800 includes several sensor nodes (e.g., sensor nodes 804a, 804b, 804c, 804d, and 804e) configured to facilitate the monitoring of moving objects (e.g., detection of aircraft 802). In some embodiments, sensor nodes 804a-804e are similar to sensor nodes 104a-104n of distributed system 100. In some embodiments, one of sensor nodes 804a-804e may be designated as a reference node and a central processing node. In some embodiments, all sensor nodes 804a-804e are configured as transmitting and receiving sensor nodes. Sensor nodes 804a-804e may be time-synchronized, as described with reference to at least Figures 4 and 5A-5C above. Furthermore, time-aligned signals may be coupled, as described with reference to at least Figure 6 above. The radar system 800 may be configured to operate across a wide range of frequencies.

[0068] Sensor nodes 804a to 804e are configured to transmit probe signals 808 in a beamforming pattern. Signals reflected from aircraft 802 may be received by the sensor nodes as data signals 810. The data signals 810 are time-aligned, combined, and processed to determine one or more parameters of aircraft 802 (e.g., aircraft distance or speed).

[0069] Figure 8 shows a single cluster of sensor nodes 804a-804e, but the radar system 800 may have several clusters. In some embodiments, each black dot in Figure 8 may be a cluster of sensor nodes. For example, black dot 804a may be a first cluster, block dot 804b may be a second cluster, and so on, each of which contains several sensor nodes. In some embodiments, such a configuration enables the detection of moving objects at very long distances and high speeds. In some embodiments, the sensor nodes or clusters may extend over hundreds of meters.

[0070] The distributed system 100 may also be implemented as a mobile sensor array system. For example, sensor nodes 104a to 104n may be designed as mobile sensor nodes, such as battery-powered or solar-powered, and may be installed in automobiles, unmanned aerial vehicles (UAVs), or other mobile devices.

[0071] Figure 8 illustrates an implementation of the distributed system 100 as a radar system, but the distributed system 100 may also be implemented as a sonar system to facilitate the monitoring of objects moving underwater (e.g., submarines). For example, sensor nodes 104a to 104n may be configured as hydrophone sensor nodes that can be installed as buoys or mobile hydrophones (e.g., inside a submarine). The hydrophone sensor nodes may be associated with a surface component that communicates with satellites and has GPS capabilities.

[0072] In yet another example, the distributed system 100 may be implemented for the oil and gas industry and mining to facilitate the detection of oil (or any other energy) and metals. For example, sensor nodes 104a-104n may be configured to operate with seismic or acoustic waveforms, and the coupled signals may be used to detect oil (or any other energy) and metals.

[0073] In some embodiments, various components or modules shown in the figures or described in the preceding paragraphs may include one or more computing devices programmed to perform the functions described herein. A computing device may include one or more electronic storage, one or more physical processors programmed with one or more computer program instructions, and / or other components. A computing device may include communication lines or communication ports to enable the exchange of information within a network or other computing platform via wired or wireless technology (e.g., Ethernet, fiber optic, coaxial cable, Wi-Fi, Bluetooth, near field communication, or other technologies). A computing device may include multiple hardware, software, and / or firmware components working together. For example, a computing device may be implemented by a cloud of a computing platform working together as a computing device. A cloud component may include control circuits configured to perform various operations necessary to carry out the disclosed embodiments. A cloud component may include cloud-based storage circuits configured to electronically store information. A cloud component may also include cloud-based input / output circuits configured to display information.

[0074] Electronic storage may include non-temporary storage media that electronically store information. The storage media of electronic storage may include (i) system storage provided integrally with a server or client device (e.g., substantially inremovable), or (ii) removable storage that can be detachably connected to a server or client device via, for example, a port (e.g., a USB port, a FireWire port) or a drive (e.g., a disk drive). Electronic storage may include one or more optically readable storage media (e.g., optical discs), magnetically readable storage media (e.g., magnetic tape, magnetic hard drives, floppy drives), charge-based storage media (e.g., EEPROM, RAM), solid-state storage media (e.g., flash drives), and / or other electronically readable storage media. Electronic storage may also include one or more virtual storage resources (e.g., cloud storage, a virtual private network, and / or other virtual storage resources). Electronic storage can store information determined by software algorithms, processors, information retrieved from servers, information retrieved from client devices, or other information that enables the functions described herein.

[0075] A processor may be programmed to provide information processing capabilities within a computing device. Therefore, a processor may include one or more of the following: a digital processor, an analog processor, digital circuits designed to process information, analog circuits designed to process information, state machines, and / or other mechanisms for electronically processing information. In some embodiments, a processor may include multiple processing units. These processing units may be physically located within the same device, or the processor may represent the processing capabilities of multiple devices working together. A processor may be programmed to execute computer program instructions to perform the functions described herein. A processor may be programmed to execute computer program instructions by software; hardware; firmware; any combination of software, hardware, or firmware; and / or other mechanisms for constituting processing capabilities on the processor.

[0076] The descriptions of the functions provided by the components or modules described herein are illustrative and not limiting, as any component or module may provide more or less functionality than described. For example, one or more components or modules may be excluded, and some or all of their functions may be provided by others. As another example, additional components or modules may be programmed to perform some or all of the functions attributed to one of the components or modules herein.

[0077] While the present invention is described in detail for illustrative purposes based on what is considered to be the most practical and preferred embodiment at present, such details are for that purpose only, and it should be understood that the present invention is not limited to the disclosed embodiments, but rather intended to cover modifications and equivalent configurations within the scope of the appended claims. For example, it should be understood that, wherever possible, one or more features of any embodiment can be combined with one or more features of any other embodiment.

[0078] This technology will be better understood by referring to the embodiments listed below.

[0079] 1: A method for bidirectional time transfer within a coherent sensor array system may include establishing a zero-hop network architecture between a plurality of sensor nodes via a processor node, wherein each of the plurality of sensor nodes includes a dedicated bidirectional time transfer (TWTT) channel, designating a master node and a plurality of slave nodes via the processor node, wherein the master node communicates with a dedicated TWTT channel for each of the plurality of slave nodes to form a noiseless timing distribution network, and distributing a master timing signal from a grandmaster clock via the master node, wherein the grandmaster clock achieves picosecond time synchronization fidelity between the master node and the plurality of slave nodes, at least within the noiseless timing distribution network.

[0080] 2: The method according to Embodiment 1, wherein the master node performs diagnostic operations to evaluate the status and health of the time synchronization accuracy between the master node and the multiple slave nodes, the time synchronization fidelity of the grandmaster clock to both the master node and the multiple slave nodes, the time offset and / or time deviation, and the frequency deviation achieved.

[0081] 3: The method according to either Embodiment 1 or 2, wherein the master node uses the state and health of the time synchronization accuracy as training data for a machine learning algorithm that adaptively improves the time synchronization of the noiseless timing distribution network.

[0082] 4: The method according to any one of embodiments 1 to 3, wherein the master node updates the time synchronization schedule while adaptive improvement is in progress.

[0083] 5: The method according to any one of embodiments 1 to 4, wherein the results of the diagnostic operation are reported to the master node as a function of time during adaptive improvement.

[0084] 6: The method according to any one of embodiments 1 to 5, wherein the master node calculates a time offset for each of the multiple slave nodes, and the master node averages the time offsets to determine the true time offset.

[0085] 7: The method according to any one of embodiments 1 to 6, wherein the master node performs longitudinal averaging of the time offset to determine the true time offset over multiple synchronization cycles.

[0086] 8: The method according to any one of embodiments 1 to 7, wherein the master node performs spatial averaging of time offsets to determine the true time offsets across multiple slave nodes at any given time.

[0087] 9: The method according to any one of embodiments 1 to 8, wherein a master node transmits a master timing signal to a plurality of slave nodes via a wired TWTT channel, and the plurality of slave nodes transmit responses via a wireless TWTT channel.

[0088] 10: The method according to any one of embodiments 1 to 9, wherein the master node sends a timestamped message instructing each of the multiple slave nodes to send a slave timing signal at a known future time, the slave timing signals are sent at a known future time and received by the master node, and the difference between the known future time and the time of reception by the master node is used to calculate a node-specific time offset that correlates with the distance between the master node and the corresponding slave node from the multiple slave nodes.

[0089] 11: The method according to any one of embodiments 1 to 10, wherein a processor node calibrates a phased array based on a true time delay between a plurality of antenna nodes, the true time delay being a node-specific time offset for each of a plurality of slave nodes on a noiseless timing distribution network, and the antenna nodes are communicably coupled via at least one of wired or wireless connections.

[0090] 12: A method according to any of embodiments 1 to 11 may further include generating a master timing signal for at least one slave node via a primary master node, wherein the master node and at least one slave node are from a plurality of sensor nodes included in a sensor array system; synchronizing at least one slave node with the master timing signal transmitted via a dedicated timing data channel via the primary master node; and combining data signals from at least one slave node via a processor node, wherein the processor node is from a plurality of sensor nodes.

[0091] 13: The method according to any one of embodiments 1 to 12, wherein the synchronous data signals of at least one slave node are combined to generate a composite signal, the composite signal having a power level greater than any of the power levels of the sensor nodes.

[0092] 14: The method of any of embodiments 1 to 13 may further include generating a synchronization window protocol via a primary master node and communicating timing signal data with at least one slave node in accordance with the synchronization window protocol.

[0093] 15: The method according to any one of embodiments 1 to 14, wherein at least one slave node continuously listens to timing signal data.

[0094] 16: The method according to any one of embodiments 1 to 15, wherein at least one slave node listens for timing signal data during a scheduled window in accordance with the synchronous window protocol.

[0095] 17: The method according to any one of embodiments 1 to 16, wherein at least one slave node adaptively determines when to listen for timing signal data in accordance with the synchronization window protocol.

[0096] 18: The method according to any one of embodiments 1 to 17, wherein at least one slave node ignores unwanted data captured during a listen window in accordance with the synchronization window protocol.

[0097] 19: A method according to any of embodiments 1 to 18 involves monitoring the primary clock drift of a grandmaster clock and the secondary clock drift of a corresponding slave clock via a primary master node, wherein the grandmaster clock is included in the primary master node and the corresponding slave clock is included in at least one slave node, and further includes updating timing signals based on the primary clock drift via the primary master node, and modifying the synchronization window protocol based on the secondary clock drift via the primary master node.

[0098] 20: The method according to any of embodiments 1 to 19 may further include determining the average secondary clock drift of a plurality of slave nodes via a primary master node, and modifying the synchronization window protocol based on the average secondary clock drift via the primary master node.

[0099] 21: The method according to any one of embodiments 1 to 20, wherein if the secondary clock drift exceeds a desired threshold, the primary master node resynchronizes at least one slave node.

[0100] 22: The method according to any one of embodiments 1 to 21, wherein the primary master node and at least one slave node operate in a zero-hop network architecture.

[0101] 23: The method according to any one of embodiments 1 to 22, wherein at least one slave node is a plurality of slave nodes connected to a primary master node using a one-to-many master-slave protocol, and the method may further include: each of the plurality of sensor nodes sharing corresponding sensor node state information with the sensor array system; synchronizing the plurality of sensor nodes based on the state information of the plurality of sensor nodes used to synchronize data signals received or transmitted by the plurality of sensor nodes; generating corresponding master timing signals for each of the plurality of slave nodes via the primary master node; and communicating corresponding master timing signals for each of the plurality of slave nodes via the primary master node through corresponding timing data channels.

[0102] 24: The method according to any of embodiments 1 to 23, wherein multiple slave nodes function as a passive sensing system using blind channel estimation and supersampling protocols, and a primary master node resynchronizes the multiple slave nodes to maintain picosecond time resolution.

[0103] 25: The method according to any one of embodiments 1 to 24, wherein multiple slave nodes and a primary master node utilize a time synchronization protocol.

[0104] 26: The method according to any one of embodiments 1 to 25, wherein multiple slave nodes perform adaptive angle of arrival adjustments on passively received signals to determine the position, bearing, and velocity of at least one target.

[0105] 27: The method according to any one of embodiments 1 to 26, wherein multiple sensor nodes are configured in a multi-static passive lighter system.

[0106] 28: The method according to any one of embodiments 1 to 27, wherein each of the multiple slave nodes represents a cluster of sensor nodes synchronized to a secondary master node, and each cluster of sensor nodes is connected to the secondary master node via a corresponding secondary timing channel, and the secondary master node synchronizes to the primary master node.

[0107] 29: The method according to any one of embodiments 1 to 28, wherein a primary master node and at least one slave node communicate via a bidirectional stateless connection.

[0108] 30: The method according to any one of embodiments 1 to 29, wherein the dedicated timing data channel is an optical fiber connection between a primary master node and at least one slave node.

[0109] 31: The method according to any one of embodiments 1 to 30, wherein the dedicated timing data channel is a wireless connection between a primary master node and at least one slave node.

[0110] 32: The method according to any one of embodiments 1 to 31, for canceling out target velocity and gravitational field data when synchronization operates on a relativistic scale.

[0111] 33: The method according to any one of embodiments 1 to 32, wherein multiple sensor nodes operate as a noise-free network.

[0112] 34: A non-temporary computer-readable medium storing a set of instructions for bidirectional time transfer in a coherent sensor array, the set of instructions, when executed by one or more processors of the device, may include one or more instructions causing the device to establish a zero-hop network architecture between a plurality of sensor nodes via a processor node, wherein each of the plurality of sensor nodes includes a dedicated bidirectional time transfer (TWTT) channel, and via the processor node, designate a master node and a plurality of slave nodes, wherein the master node communicates with the dedicated TWTT channel for each of the plurality of slave nodes to form a noiseless timing distribution network, and via the master node, distribute a master timing signal from a grandmaster clock, wherein the grandmaster clock achieves picosecond time synchronization fidelity between the master node and the plurality of slave nodes, at least within the noiseless timing distribution network.

[0113] 35: A non-temporal computer-readable medium according to Embodiment 34, wherein the master node performs diagnostic operations to evaluate the status and health of the time synchronization accuracy between the master node and the multiple slave nodes, the time synchronization fidelity of the grandmaster clock to both the master node and the multiple slave nodes, the time offset and / or time deviation, and the frequency deviation achieved.

[0114] 36: A non-transient computer-readable medium according to either embodiment 34 or 35, wherein the master node uses the state and health of the time synchronization accuracy as training data for a machine learning algorithm that adaptively improves the time synchronization of a noiseless timing distribution network.

[0115] 37: A non-transient computer-readable medium according to any of embodiments 34 to 36, wherein the master node updates the time synchronization schedule while adaptive improvement is in progress.

[0116] 38: A non-temporary computer-readable medium according to any of embodiments 34 to 37, wherein the results of a diagnostic operation are reported to the master node as a function of time during adaptive improvement.

[0117] 39: A non-temporary computer-readable medium according to any of embodiments 34 to 38, wherein the master node calculates a time offset for each of a plurality of slave nodes, and the master node averages the time offsets to determine the true time offset.

[0118] 40: A non-temporary computer-readable medium according to any of embodiments 34 to 39, wherein the master node performs longitudinal averaging of time offsets to determine the true time offset over multiple synchronization cycles.

[0119] 41: A non-temporary computer-readable medium according to any one of embodiments 34 to 40, wherein the master node performs spatial averaging of time offsets to determine the true time offset across multiple slave nodes at any given time.

[0120] 42: A non-transient computer-readable medium according to any one of embodiments 34 to 41, wherein a master node transmits a master timing signal to a plurality of slave nodes via a wired TWTT channel, and the plurality of slave nodes transmit responses via a wireless TWTT channel.

[0121] 43: A non-temporary computer-readable medium according to any of embodiments 34 to 42, wherein a master node sends a timestamped message instructing each of a plurality of slave nodes to send a slave timing signal at a known future time, the slave timing signals are sent at a known future time and received by the master node, and the difference between the known future time and the time of reception by the master node is used to calculate a node-specific time offset that correlates with the distance between the master node and the corresponding slave node from the plurality of slave nodes.

[0122] 44: A non-transient computer-readable medium according to any one of embodiments 34 to 43, wherein a processor node calibrates a phased array based on true time delays between multiple antenna data channels, the true time delay being a node-specific time offset for each of multiple slave nodes on a noiseless timing distribution network, and the antenna nodes are communicably coupled via at least one of wired or wireless connections.

[0123] 45: A non-temporary computer-readable medium according to any one of embodiments 34 to 44, wherein one or more instructions cause the device to generate a master timing signal for at least one slave node via a primary master node, wherein the master node and at least one slave node are from a plurality of sensor nodes included in a coherent sensor array; to synchronize at least one slave node with the master timing signal transmitted via a dedicated timing data channel via the primary master node; and to combine data signals from at least one slave node via a processor node, wherein the processor node is from a plurality of sensor nodes.

[0124] 46: A non-transient computer-readable medium according to any of embodiments 34 to 45, wherein combining the synchronous data signals of at least one slave node generates a composite signal, the composite signal having a power level greater than any of the power levels of the sensor nodes.

[0125] 47: A non-temporary computer-readable medium according to any embodiment 34 to 46, wherein one or more instructions cause the device to further generate a synchronous window protocol via a primary master node and to communicate timing signal data with at least one slave node in accordance with the synchronous window protocol.

[0126] 48: At least one slave node continuously listens to timing signal data in a non-transient computer-readable medium as described in any of embodiments 34 to 47.

[0127] 49: A non-transient computer-readable medium according to any of embodiments 34 to 48, wherein at least one slave node listens to timing signal data during a scheduled window in accordance with a synchronization window protocol.

[0128] 50: A non-transient computer-readable medium according to any one of embodiments 34 to 49, wherein at least one slave node adaptively determines when to listen for timing signal data in accordance with a synchronization window protocol.

[0129] 51: A non-transient computer-readable medium according to any of embodiments 34 to 50, wherein at least one slave node ignores unwanted data captured during a listening window in accordance with a synchronization window protocol.

[0130] 52: A non-temporary computer-readable medium according to any embodiment 34 to 51, wherein one or more instructions monitor the primary clock drift of a grandmaster clock and the secondary clock drift of a corresponding slave clock via a primary master node, the grandmaster clock being included in the primary master node and the corresponding slave clock being included in at least one slave node, and further cause the device to update timing signals based on the primary clock drift via the primary master node and modify the synchronization window protocol based on the secondary clock drift via the primary master node.

[0131] 53: A non-temporary computer-readable medium according to any embodiment 34 to 52, wherein one or more instructions cause the device to further determine the average secondary clock drift of a plurality of slave nodes via a primary master node, and to modify the synchronization window protocol based on the average secondary clock drift via the primary master node.

[0132] 54: A non-transient computer-readable medium according to any of embodiments 34 to 53, wherein if the secondary clock drift exceeds a desired threshold, the primary master node resynchronizes at least one slave node.

[0133] 55: A non-transient computer-readable medium according to any of embodiments 34 to 54, wherein the primary master node and at least one slave node operate in a zero-hop network architecture.

[0134] 56: A non-temporary computer-readable medium according to any of embodiments 34 to 55, in which one or more instructions can cause a device to: share corresponding sensor node state information with a sensor array system by each of the multiple sensor nodes; synchronize the multiple sensor nodes based on the state information of the multiple sensor nodes in order to synchronize data signals received or transmitted by the multiple sensor nodes; generate corresponding master timing signals for each of the multiple slave nodes via the primary master node; and communicate corresponding master timing signals for each of the multiple slave nodes via the primary master node through corresponding timing data channels.

[0135] 57: A non-transient computer-readable medium according to any of embodiments 34 to 56, wherein multiple slave nodes function as a passive sensing system using blind channel estimation and supersampling protocols, and a primary master node resynchronizes the multiple slave nodes to maintain picosecond time resolution.

[0136] 58: A non-temporary computer-readable medium according to any of embodiments 34 to 57, wherein multiple slave nodes and a primary master node utilize a time synchronization protocol.

[0137] 59: A non-transient computer-readable medium according to any of embodiments 34 to 58, wherein multiple slave nodes perform adaptive angle of arrival adjustments on passively received signals to determine the position, bearing, and velocity of at least one target.

[0138] 60: A non-temporary computer-readable medium according to any of embodiments 34 to 59, wherein multiple sensor nodes constitute a multi-static passive lighter system.

[0139] 61: A non-transient computer-readable medium according to any of embodiments 34 to 60, wherein each of a plurality of slave nodes represents a cluster of sensor nodes synchronized to a secondary master node, and each cluster of sensor nodes is connected to the secondary master node via a corresponding secondary timing channel, and the secondary master node synchronizes to the primary master node.

[0140] 62: A non-temporary computer-readable medium according to any one of embodiments 34 to 61, wherein a primary master node and at least one slave node communicate via a bidirectional stateless connection.

[0141] 63: A non-transient computer-readable medium according to any of embodiments 34 to 62, wherein the dedicated timing data channel is an optical fiber connection between a primary master node and at least one slave node.

[0142] 64: A non-transient computer-readable medium according to any of embodiments 34 to 63, wherein the dedicated timing data channel is a wireless connection between a primary master node and at least one slave node.

[0143] 65: A non-temporal computer-readable medium according to any of embodiments 34 to 64, which cancels out target velocity and gravitational field data when synchronization operates on a relativistic scale.

[0144] 66: A non-transient computer-readable medium according to any one of embodiments 34 to 65, wherein multiple sensor nodes operate as a noise-free network.

[0145] 67: A system for bidirectional time transfer in a coherent sensor array may include one or more processors configured to establish a zero-hop network architecture between a plurality of sensor nodes via a processor node, each of the plurality of sensor nodes having a dedicated bidirectional time transfer (TWTT) channel, and to designate a master node and a plurality of slave nodes via the processor node, the master node communicating with a dedicated TWTT channel for each of the plurality of slave nodes to form a noiseless timing distribution network, and to distribute a master timing signal from a grandmaster clock via the master node, the grandmaster clock achieving picosecond time synchronization fidelity between the master node and the plurality of slave nodes, at least within the noiseless timing distribution network.

[0146] 68: The system according to Embodiment 67, wherein the master node performs diagnostic operations to evaluate the status and health of the time synchronization accuracy between the master node and the multiple slave nodes, the time synchronization fidelity of the grandmaster clock to both the master node and the multiple slave nodes, the time offset and / or time deviation, and the frequency deviation achieved.

[0147] 69: The system according to either embodiment 67 or 68, wherein the master node uses the state and health of the time synchronization accuracy as training data for a machine learning algorithm that adaptively improves the time synchronization of the noiseless timing distribution network.

[0148] 70: The system according to any one of embodiments 67 to 69, wherein the master node updates the time synchronization schedule while adaptive improvement is in progress.

[0149] 71: The system according to any one of embodiments 67 to 70, wherein the results of the diagnostic operation are reported to the master node as a function of time during adaptive improvement.

[0150] 72: The system according to any one of embodiments 67 to 71, wherein the master node calculates a time offset for each of the multiple slave nodes, and the master node averages the time offsets to determine the true time offset.

[0151] 73: The system according to any one of embodiments 67 to 72, wherein the master node performs longitudinal averaging of time offsets to determine the true time offset over multiple synchronization cycles.

[0152] 74: The system according to any one of embodiments 67 to 73, wherein the master node performs spatial averaging of time offsets to determine the true time offset across multiple slave nodes at any given time.

[0153] 75: The system according to any one of embodiments 67 to 74, wherein a master node transmits a master timing signal to a plurality of slave nodes via a wired TWTT channel, and the plurality of slave nodes transmit responses via a wireless TWTT channel.

[0154] 76: The system according to any one of embodiments 67 to 75, wherein a master node sends a timestamped message instructing each of a plurality of slave nodes to send a slave timing signal at a known future time, the slave timing signals are sent at a known future time and received by the master node, and the difference between the known future time and the time of reception by the master node is used to calculate a node-specific time offset that correlates with the distance between the master node and the corresponding slave node from the plurality of slave nodes.

[0155] 77: The system according to any one of embodiments 67 to 76, wherein a processor node calibrates a phased array based on true time delays between multiple antenna data channels, the true time delay being a node-specific time offset for each of multiple slave nodes on a noiseless timing distribution network, and the antenna nodes are communicably coupled via at least one of wired or wireless connections.

[0156] 78: The system according to any one of embodiments 67 to 77, further configured to generate a master timing signal for at least one slave node via a primary master node, wherein the master node and at least one slave node are from a plurality of sensor nodes included in a sensor array system; to synchronize at least one slave node with a master timing signal transmitted via a dedicated timing data channel via the primary master node; and to combine data signals from at least one slave node via a processor node, wherein the processor node is from a plurality of sensor nodes.

[0157] 79: The system according to any one of embodiments 67 to 78, wherein the synchronous data signals of at least one slave node are combined to produce a composite signal, the composite signal having a power level greater than any of the power levels of the sensor nodes.

[0158] 80: The system according to any one of embodiments 67 to 79, further configured to generate a synchronous window protocol via a primary master node and to communicate timing signal data with at least one slave node in accordance with the synchronous window protocol.

[0159] 81: The system according to any one of embodiments 67 to 80, wherein at least one slave node continuously listens to timing signal data.

[0160] 82: The system according to any one of embodiments 67 to 81, wherein at least one slave node listens for timing signal data during a scheduled window in accordance with the synchronous window protocol.

[0161] 83: The system according to any one of embodiments 67 to 82, wherein at least one slave node adaptively determines when to listen for timing signal data in accordance with the synchronization window protocol.

[0162] 84: The system according to any one of embodiments 67 to 83, wherein at least one slave node ignores unwanted data captured during a listen window in accordance with the synchronization window protocol.

[0163] 85: A system according to any one of embodiments 67 to 84, wherein one or more processors monitor the primary clock drift of a grandmaster clock and the secondary clock drift of a corresponding slave clock via a primary master node, the grandmaster clock being included in the primary master node and the corresponding slave clock being included in at least one slave node, and further configured to update timing signals based on the primary clock drift via the primary master node and to modify the synchronization window protocol based on the secondary clock drift via the primary master node.

[0164] 86: The system according to any one of embodiments 67 to 85, further configured to determine the average secondary clock drift of a plurality of slave nodes via a primary master node, and to modify the synchronization window protocol based on the average secondary clock drift via the primary master node.

[0165] 87: The system according to any one of embodiments 67 to 86, wherein if the secondary clock drift exceeds a desired threshold, the primary master node resynchronizes at least one slave node.

[0166] 88: The system according to any one of embodiments 67 to 87, wherein the primary master node and at least one slave node operate in a zero-hop network architecture.

[0167] 89: The system according to any one of embodiments 67 to 88, wherein one or more processors are configured to share the state information of a corresponding sensor node with the sensor array system by each of the multiple sensor nodes, when at least one of the multiple slave nodes is a plurality of slave nodes connected to a primary master node using a one-to-many master-slave protocol, to synchronize the multiple sensor nodes based on the state information of the multiple sensor nodes in order to synchronize data signals received or transmitted by the multiple sensor nodes, to generate a corresponding master timing signal for each of the multiple slave nodes via the primary master node, and to communicate the corresponding master timing signal for each of the multiple slave nodes via the primary master node through a corresponding timing data channel.

[0168] 90: The system according to any one of embodiments 67 to 89, wherein multiple slave nodes function as a passive sensing system using blind channel estimation and supersampling protocols, and a primary master node resynchronizes the multiple slave nodes to maintain picosecond time resolution.

[0169] 91: A system according to any one of embodiments 67 to 90, wherein multiple slave nodes and a primary master node utilize a time synchronization protocol.

[0170] 92: The system according to any one of embodiments 67 to 91, wherein multiple slave nodes perform adaptive angle of arrival adjustments on passively received signals to determine the position, bearing, and velocity of at least one target.

[0171] 93: The system according to any one of embodiments 67 to 92, wherein multiple sensor nodes are configured in a multi-static passive lighter system.

[0172] 94: The system according to any one of embodiments 67 to 93, wherein each of the multiple slave nodes represents a cluster of sensor nodes synchronized to a secondary master node, and each cluster of sensor nodes is connected to the secondary master node via a corresponding secondary timing channel, and the secondary master node synchronizes to the primary master node.

[0173] 95: The system according to any one of embodiments 67 to 94, wherein a primary master node and at least one slave node communicate via a bidirectional stateless connection.

[0174] 96: The system according to any one of embodiments 67 to 95, wherein the dedicated timing data channel is an optical fiber connection between a primary master node and at least one slave node.

[0175] 97: The system according to any one of embodiments 67 to 96, wherein the dedicated timing data channel is a wireless connection between a primary master node and at least one slave node.

[0176] 98: A system according to any one of embodiments 67 to 97, which cancels out target velocity and gravitational field data when synchronization operates on a relativistic scale.

[0177] 99: A system according to any one of embodiments 67 to 98, wherein multiple sensor nodes operate as a noise-free network.

Claims

1. A method for bidirectional time transfer within a coherent sensor array system, Establishing a zero-hop network architecture between multiple sensor nodes via a processor node, wherein each of the multiple sensor nodes includes a dedicated bidirectional time-to-time (TWTT) channel, The process involves designating a master node and a plurality of slave nodes via the aforementioned processor node, wherein the master node communicates with a dedicated TWTT channel for each of the plurality of slave nodes to form a noiseless timing distribution network. Distributing the master timing signal from the grandmaster clock via the master node, wherein the grandmaster clock achieves picosecond time synchronization fidelity between the master node and the plurality of slave nodes, at least within the noiseless timing distribution network. Methods that include...

2. The method according to claim 1, wherein the master node performs diagnostic operations to evaluate the state and health of the time synchronization accuracy between the master node and the plurality of slave nodes, the time synchronization fidelity, time offset and / or time deviation of the grandmaster clock to both the master node and the plurality of slave nodes, and the frequency deviation achieved.

3. The method according to claim 2, wherein the master node uses the state and health of the time synchronization accuracy as training data for a machine learning algorithm that adaptively improves the time synchronization of the noiseless timing distribution network.

4. The method according to claim 3, wherein the master node updates the time synchronization schedule during the adaptive improvement.

5. The method according to claim 3, wherein the results of the diagnostic operation are reported to the master node as a function of time during the adaptive improvement.

6. The method according to claim 1, wherein the master node calculates a time offset for each of the plurality of slave nodes, and the master node averages the time offsets to determine the true time offset.

7. The method according to claim 6, wherein the master node performs longitudinal averaging of the time offset to determine the true time offset over a plurality of synchronization cycles.

8. The method according to claim 6, wherein the master node performs spatial averaging of the time offset to determine the true time offset across the plurality of slave nodes at any given time.

9. The method according to claim 1, wherein the master node transmits the master timing signal to the plurality of slave nodes via a wired TWTT channel, and the plurality of slave nodes transmit responses via a wireless TWTT channel.

10. The method according to claim 1, wherein the master node sends a timestamped message instructing each of the plurality of slave nodes to send a slave timing signal at a known future time, the slave timing signal is sent at the known future time and received by the master node, and the difference between the known future time and the time of reception by the master node is used to calculate a node-specific time offset that correlates with the distance between the master node and the corresponding slave node from the plurality of slave nodes.

11. The method according to claim 10, wherein the processor node calibrates a phased array based on a true time delay between a plurality of antenna nodes, the true time delay being a node-specific time offset for each of the plurality of slave nodes on the noiseless timing distribution network, and the antenna nodes are communicably coupled via at least one of wired or wireless connections.

12. To generate a master timing signal for at least one slave node via a primary master node, wherein the master node and the at least one slave node are from a plurality of sensor nodes included in the sensor array system, The primary master node synchronizes the master timing signal transmitted via a dedicated timing data channel with the at least one slave node, The process involves combining data signals from at least one slave node via the processor node, wherein the processor node is from the plurality of sensor nodes. The method according to claim 1, further comprising:

13. The method according to claim 12, wherein combining the synchronization data signals of at least one slave node generates a composite signal, the composite signal having a power level greater than any of the power levels of the sensor nodes.

14. The primary master node generates a synchronization window protocol, Communicating timing signal data with the at least one slave node in accordance with the aforementioned synchronization window protocol, The method according to claim 12, further comprising:

15. The method according to claim 14, wherein the at least one slave node continuously listens to timing signal data.

16. The method according to claim 14, wherein the at least one slave node listens to timing signal data during a scheduled window in accordance with the synchronization window protocol.

17. The method according to claim 14, wherein the at least one slave node adaptively determines when to listen for timing signal data in accordance with the synchronization window protocol.

18. The method according to claim 14, wherein the at least one slave node ignores unwanted data captured during the listen window in accordance with the synchronization window protocol.

19. Monitoring the primary clock drift of the grandmaster clock and the secondary clock drift of the corresponding slave clock via the primary master node, wherein the grandmaster clock is included in the primary master node and the corresponding slave clock is included in at least one slave node. The timing signal is updated based on the primary clock drift via the primary master node, The primary master node modifies the synchronization window protocol based on the secondary clock drift, The method according to claim 14, further comprising:

20. The average secondary clock drift of multiple slave nodes is determined via the primary master node, The synchronization window protocol is modified based on the average secondary clock drift via the primary master node, The method according to claim 19, further comprising:

21. The method according to claim 19, wherein if the secondary clock drift exceeds a desired threshold, the primary master node resynchronizes the at least one slave node.

22. The method according to claim 12, wherein the primary master node and the at least one slave node operate in a zero-hop network architecture.

23. The at least one slave node is a plurality of slave nodes connected to the primary master node using a one-to-many master-slave protocol, and the method is Each of the multiple sensor nodes shares the state information of the corresponding sensor node with the sensor array system, Synchronizing the multiple sensor nodes based on the state information of the multiple sensor nodes used to synchronize data signals received or transmitted by the multiple sensor nodes, The primary master node generates a corresponding master timing signal for each of the plurality of slave nodes, The primary master node communicates the corresponding master timing signal for each of the plurality of slave nodes via the corresponding timing data channel. The method according to claim 12, further comprising:

24. The method according to claim 23, wherein the plurality of slave nodes function as a passive sensing system using blind channel estimation and supersampling protocols, and the primary master node resynchronizes the plurality of slave nodes to maintain picosecond time resolution.

25. The method according to claim 24, wherein the plurality of slave nodes and the primary master node utilize a time synchronization protocol.

26. The method according to claim 24, wherein the plurality of slave nodes perform adaptive angle of arrival adjustments on passively received signals to determine the position, bearing, and velocity of at least one target.

27. The method according to claim 23, wherein the plurality of sensor nodes are configured in a multistatic passive lighter system.

28. The method according to claim 23, wherein each of the plurality of slave nodes represents a cluster of sensor nodes synchronized with a secondary master node, each of the clusters of sensor nodes is connected to the secondary master node via a corresponding secondary timing channel, and the secondary master node synchronizes with the primary master node.

29. The method according to claim 12, wherein the primary master node and the at least one slave node communicate via a bidirectional stateless connection.

30. The method according to claim 12, wherein the dedicated timing data channel is an optical fiber connection between the primary master node and the at least one slave node.

31. The method according to claim 12, wherein the dedicated timing data channel is a wireless connection between the primary master node and the at least one slave node.

32. The method according to claim 12, wherein the synchronization cancels out target velocity and gravitational field data when the synchronization operates on a relativistic scale.

33. The method according to claim 12, wherein the plurality of sensor nodes operate as a noise-free network.

34. A non-temporary computer-readable medium for storing a set of instructions for bidirectional time transfer within a coherent sensor array, wherein the set of instructions is When executed by one or more processors of a device, Establishing a zero-hop network architecture between multiple sensor nodes via a processor node, wherein each of the multiple sensor nodes includes a dedicated bidirectional time-to-time (TWTT) channel, The process involves designating a master node and a plurality of slave nodes via the aforementioned processor node, wherein the master node communicates with a dedicated TWTT channel for each of the plurality of slave nodes to form a noiseless timing distribution network. Distributing the master timing signal from the grandmaster clock via the master node, wherein the grandmaster clock achieves picosecond time synchronization fidelity between the master node and the plurality of slave nodes, at least within the noiseless timing distribution network. One or more commands to cause the device to perform the above Non-temporary computer-readable media, including [specific examples of such media].

35. The non-temporary computer-readable medium according to claim 34, wherein the master node performs diagnostic operations to evaluate the state and health of the time synchronization accuracy between the master node and the plurality of slave nodes, the time synchronization fidelity, time offset and / or time deviation of the grandmaster clock to both the master node and the plurality of slave nodes, and the frequency deviation achieved.

36. The non-temporary computer-readable medium according to claim 35, wherein the master node uses the state and health of the time synchronization accuracy as training data for a machine learning algorithm that adaptively improves the time synchronization of the noiseless timing distribution network.

37. The non-temporary computer-readable medium according to claim 36, wherein the master node updates the time synchronization schedule during the adaptive improvement.

38. The non-temporary computer-readable medium according to claim 36, wherein the results of the diagnostic operation are reported to the master node as a function of time during the adaptive improvement.

39. The non-temporary computer-readable medium according to claim 34, wherein the master node calculates a time offset for each of the plurality of slave nodes, and the master node averages the time offsets to determine the true time offset.

40. The non-temporary computer-readable medium according to claim 39, wherein the master node performs longitudinal averaging of the time offset to determine the true time offset over a plurality of synchronization cycles.

41. The non-temporal computer-readable medium according to claim 39, wherein the master node performs spatial averaging of the time offset to determine the true time offset across the plurality of slave nodes at any given time.

42. The non-transient computer-readable medium according to claim 34, wherein the master node transmits the master timing signal to the plurality of slave nodes via a wired TWTT channel, and the plurality of slave nodes transmit responses via a wireless TWTT channel.

43. The non-temporary computer-readable medium according to claim 34, wherein the master node sends a timestamped message instructing each of the plurality of slave nodes to transmit a slave timing signal at a known future time, the slave timing signal is transmitted at the known future time and received by the master node, and the difference between the known future time and the time of reception by the master node is used to calculate a node-specific time offset that correlates with the distance between the master node and the corresponding slave node from the plurality of slave nodes.

44. The non-transient computer-readable medium according to claim 43, wherein the processor node calibrates a phased array based on a true time delay between a plurality of antenna data channels, the true time delay being a node-specific time offset for each of the plurality of slave nodes on the noiseless timing distribution network, and the antenna nodes are communicably coupled via at least one of wired or wireless connections.

45. The one or more instructions mentioned above, To generate a master timing signal for at least one slave node via a primary master node, wherein the master node and the at least one slave node are from a plurality of sensor nodes included in the coherent sensor array, The primary master node synchronizes the master timing signal transmitted via a dedicated timing data channel with the at least one slave node, The process involves combining data signals from at least one slave node via the processor node, wherein the processor node is from the plurality of sensor nodes. A non-temporary computer-readable medium according to claim 34, further causing the device to perform the same action.

46. The non-transient computer-readable medium according to claim 45, wherein combining the synchronization data signals of at least one slave node generates a composite signal, the composite signal having a power level greater than any of the power levels of the sensor nodes.

47. The one or more instructions mentioned above, The primary master node generates a synchronization window protocol, Communicating timing signal data with the at least one slave node in accordance with the aforementioned synchronization window protocol, A non-temporary computer-readable medium according to claim 45, further causing the device to perform the same action.

48. The non-transient computer-readable medium according to claim 47, wherein at least one slave node continuously listens to timing signal data.

49. The non-transient computer-readable medium according to claim 47, wherein at least one slave node listens to timing signal data during a scheduled window in accordance with the synchronization window protocol.

50. The non-transient computer-readable medium according to claim 47, wherein the at least one slave node adaptively determines when to listen for timing signal data in accordance with the synchronization window protocol.

51. The non-transient computer-readable medium according to claim 47, wherein at least one slave node ignores unwanted data captured during the listening window in accordance with the synchronization window protocol.

52. The one or more instructions mentioned above, Monitoring the primary clock drift of the grandmaster clock and the secondary clock drift of the corresponding slave clock via the primary master node, wherein the grandmaster clock is included in the primary master node and the corresponding slave clock is included in at least one slave node. The timing signal is updated based on the primary clock drift via the primary master node, The primary master node modifies the synchronization window protocol based on the secondary clock drift, A non-temporary computer-readable medium according to claim 47, further causing the device to perform the same action.

53. The one or more instructions mentioned above, The average secondary clock drift of multiple slave nodes is determined via the primary master node, The synchronization window protocol is modified based on the average secondary clock drift via the primary master node, A non-temporary computer-readable medium according to claim 52, wherein the device further performs the following.

54. The non-transient computer-readable medium according to claim 52, wherein if the secondary clock drift exceeds a desired threshold, the primary master node resynchronizes the at least one slave node.

55. The non-transient computer-readable medium according to claim 45, wherein the primary master node and the at least one slave node operate in a zero-hop network architecture.

56. When the one or more instructions are such that the at least one slave node is a plurality of slave nodes connected to the primary master node using a one-to-many master-slave protocol, the method Each of the multiple sensor nodes shares the state information of the corresponding sensor node with the sensor array system, To synchronize the data signals received or transmitted by the plurality of sensor nodes, the plurality of sensor nodes are synchronized based on the state information of the plurality of sensor nodes, The primary master node generates a corresponding master timing signal for each of the plurality of slave nodes, The primary master node communicates the corresponding master timing signal for each of the plurality of slave nodes via the corresponding timing data channel. A non-temporary computer-readable medium according to claim 45, which can cause the device to perform the operation.

57. The non-transient computer-readable medium according to claim 56, wherein the plurality of slave nodes function as a passive sensing system using blind channel estimation and supersampling protocols, and the primary master node resynchronizes the plurality of slave nodes to maintain picosecond time resolution.

58. The non-temporary computer-readable medium according to claim 57, wherein the plurality of slave nodes and the primary master node utilize a time synchronization protocol.

59. The non-transient computer-readable medium according to claim 57, wherein the plurality of slave nodes perform adaptive angle of arrival adjustments on passively received signals to determine the position, bearing, and velocity of at least one target.

60. The non-temporary computer-readable medium according to claim 56, wherein the plurality of sensor nodes constitute a multi-static passive lighter system.

61. The non-temporary computer-readable medium according to claim 56, wherein each of the plurality of slave nodes represents a cluster of sensor nodes synchronized to a secondary master node, each of the cluster of sensor nodes is connected to the secondary master node via a corresponding secondary timing channel, and the secondary master node synchronizes to the primary master node.

62. The non-temporary computer-readable medium according to claim 45, wherein the primary master node and the at least one slave node communicate via a bidirectional stateless connection.

63. The non-transient computer-readable medium according to claim 45, wherein the dedicated timing data channel is an optical fiber connection between the primary master node and the at least one slave node.

64. The non-transient computer-readable medium according to claim 45, wherein the dedicated timing data channel is a wireless connection between the primary master node and the at least one slave node.

65. The non-temporal computer-readable medium according to claim 45, which cancels out target velocity and gravitational field data when the synchronization operates on a relativistic scale.

66. The non-temporary computer-readable medium according to claim 45, wherein the plurality of sensor nodes operate as a noise-free network.

67. A system for bidirectional time transfer within a coherent sensor array, One or more processors, Establishing a zero-hop network architecture between multiple sensor nodes via a processor node, wherein each of the multiple sensor nodes includes a dedicated bidirectional time-to-time (TWTT) channel, The process involves designating a master node and a plurality of slave nodes via the aforementioned processor node, wherein the master node communicates with a dedicated TWTT channel for each of the plurality of slave nodes to form a noiseless timing distribution network. Distributing the master timing signal from the grandmaster clock via the master node, wherein the grandmaster clock achieves picosecond time synchronization fidelity between the master node and the plurality of slave nodes, at least within the noiseless timing distribution network. A processor configured to perform A system equipped with these features.

68. The system according to claim 67, wherein the master node performs diagnostic operations to evaluate the state and health of the time synchronization accuracy between the master node and the plurality of slave nodes, the time synchronization fidelity, time offset and / or time deviation of the grandmaster clock to both the master node and the plurality of slave nodes, and the frequency deviation achieved.

69. The system according to claim 68, wherein the master node uses the state and health of the time synchronization accuracy as training data for a machine learning algorithm that adaptively improves the time synchronization of the noiseless timing distribution network.

70. The system according to claim 69, wherein the master node updates the time synchronization schedule during the adaptive improvement.

71. The system according to claim 69, wherein the results of the diagnostic operation are reported to the master node as a function of time during the adaptive improvement.

72. The system according to claim 67, wherein the master node calculates a time offset for each of the plurality of slave nodes, and the master node averages the time offsets to determine the true time offset.

73. The system according to claim 72, wherein the master node performs longitudinal averaging of the time offset to determine the true time offset over a plurality of synchronization cycles.

74. The system according to claim 72, wherein the master node performs spatial averaging of the time offset to determine the true time offset across the plurality of slave nodes at any given time.

75. The system according to claim 67, wherein the master node transmits the master timing signal to the plurality of slave nodes via a wired TWTT channel, and the plurality of slave nodes transmit responses via a wireless TWTT channel.

76. The system according to claim 67, wherein the master node sends a timestamped message instructing each of the plurality of slave nodes to transmit a slave timing signal at a known future time, the slave timing signal is transmitted at the known future time and received by the master node, and the difference between the known future time and the time of reception by the master node is used to calculate a node-specific time offset that correlates with the distance between the master node and the corresponding slave node from the plurality of slave nodes.

77. The system according to claim 76, wherein the processor node calibrates a phased array based on true time delays between a plurality of antenna data channels, the true time delay being a node-specific time offset for each of the plurality of slave nodes on the noiseless timing distribution network, and the antenna nodes are communicably coupled via at least one of wired or wireless connections.

78. The one or more processors described above To generate a master timing signal for at least one slave node via a primary master node, wherein the master node and the at least one slave node are from a plurality of sensor nodes included in the sensor array system, The primary master node synchronizes the master timing signal transmitted via a dedicated timing data channel with the at least one slave node, The process involves combining data signals from at least one slave node via the processor node, wherein the processor node is from the plurality of sensor nodes. The system according to claim 67, further configured to perform the following:

79. The system according to claim 78, wherein combining the synchronization data signals of at least one slave node generates a composite signal, the composite signal having a power level greater than any of the power levels of the sensor nodes.

80. The one or more processors described above The primary master node generates a synchronization window protocol, Communicating timing signal data with the at least one slave node in accordance with the aforementioned synchronization window protocol, The system according to claim 78, further configured to perform the following:

81. The system according to claim 80, wherein the at least one slave node continuously listens to timing signal data.

82. The system according to claim 80, wherein the at least one slave node listens to timing signal data during a scheduled window in accordance with the synchronization window protocol.

83. The system according to claim 80, wherein the at least one slave node adaptively determines when to listen for timing signal data in accordance with the synchronization window protocol.

84. The system according to claim 80, wherein the at least one slave node ignores unwanted data captured during the listening window in accordance with the synchronization window protocol.

85. The one or more processors described above Monitoring the primary clock drift of the grandmaster clock and the secondary clock drift of the corresponding slave clock via the primary master node, wherein the grandmaster clock is included in the primary master node and the corresponding slave clock is included in at least one slave node. The timing signal is updated based on the primary clock drift via the primary master node, The primary master node modifies the synchronization window protocol based on the secondary clock drift, The system according to claim 80, further configured to perform the following:

86. The one or more processors described above The average secondary clock drift of multiple slave nodes is determined via the primary master node, The synchronization window protocol is modified based on the average secondary clock drift via the primary master node, The system according to claim 85, further configured to perform the following:

87. The system according to claim 85, wherein if the secondary clock drift exceeds a desired threshold, the primary master node resynchronizes the at least one slave node.

88. The system according to claim 78, wherein the primary master node and the at least one slave node operate in a zero-hop network architecture.

89. When the one or more processors are such that the at least one slave node is a plurality of slave nodes connected to the primary master node using a one-to-many master-slave protocol, Each of the multiple sensor nodes shares the state information of the corresponding sensor node with the sensor array system, To synchronize the data signals received or transmitted by the plurality of sensor nodes, the plurality of sensor nodes are synchronized based on the state information of the plurality of sensor nodes, The primary master node generates a corresponding master timing signal for each of the plurality of slave nodes, The primary master node communicates the corresponding master timing signal for each of the plurality of slave nodes via the corresponding timing data channel. The system according to claim 78, configured to perform the following:

90. The system according to claim 89, wherein the plurality of slave nodes function as a passive sensing system using blind channel estimation and supersampling protocols, and the primary master node resynchronizes the plurality of slave nodes to maintain picosecond time resolution.

91. The system according to claim 90, wherein the plurality of slave nodes and the primary master node utilize a time synchronization protocol.

92. The system according to claim 90, wherein the plurality of slave nodes perform adaptive angle of arrival adjustments on passively received signals to determine the position, bearing, and velocity of at least one target.

93. The system according to claim 89, wherein the plurality of sensor nodes are configured as a multi-static passive lighter system.

94. The system according to claim 89, wherein each of the plurality of slave nodes represents a cluster of sensor nodes synchronized with a secondary master node, each of the cluster of sensor nodes is connected to the secondary master node via a corresponding secondary timing channel, and the secondary master node synchronizes with the primary master node.

95. The system according to claim 78, wherein the primary master node and the at least one slave node communicate via a bidirectional stateless connection.

96. The system according to claim 78, wherein the dedicated timing data channel is an optical fiber connection between the primary master node and the at least one slave node.

97. The system according to claim 78, wherein the dedicated timing data channel is a wireless connection between the primary master node and the at least one slave node.

98. The system according to claim 78, wherein the synchronization cancels out target velocity and gravitational field data when the synchronization operates on a relativistic scale.

99. The system according to claim 78, wherein the plurality of sensor nodes operate as a noise-free network.

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