Patent Description:
The invention relates generally to range finding systems, which can include Global Navigation Satellite Systems (GNSS) Receivers. More specifically, the invention relates to anomaly detection in a multiple antenna system that utilizes a known or measured baseline between antennas.

In range finding applications, a receiver can utilize information extracted from messages received from one or more transmitters to determine the transit time of each message. A distance to each transmitter can be determined from the transit time given the known propagation speed of electromagnetic radiation, and a position of the receiver, at least relative to the transmitters, can be determined via multi-lateration. A well-known example of a range finding application is the Global Positioning System. <CIT> discloses a method and an apparatus for detecting and correcting anomalous measurements in a satellite navigation receiver. Anomalous measurements are detected using the redundancy of observed satellite signals, or by analyzing the relationship between phase measurements at two frequencies when using dual frequency receivers. Upon determination that an anomalous measurement exists, the particular channel on which the anomalous measurement has occurred is determined. In addition, the extent of the anomalous measurement is estimated to produce an estimated error value. This information may then be used by the satellite navigation receiver in order to increase the accuracy of a navigation task. <CIT> discloses a global navigation system that includes a first navigation receiver located in a rover and a second navigation receiver located in a base station. Single differences of measurements of satellite signals received at the two receivers are calculated and compared to single differences derived from an observation model. Anomalous measurements are detected and removed prior to performing computations for determining the output position of the rover and resolving integer ambiguities. Detection criteria are based on the residuals between the calculated and the derived single differences. For resolving integer ambiguities, computations based on Cholessky information Kalman filters and Householder transformations are advantageously applied. Changes in the state of the satellite constellation from one epoch to another are included in the computations. <CIT> discloses a method and system for navigating an unmanned aerial vehicle (UAV) for aerial refueling. A system processor in the UAV receives navigation data from a tanker aircraft and calculates a plurality of relative navigation solutions with respect to the tanker aircraft. The system processor compares the plurality of relative navigation solutions to identify any inconsistent solutions. The inconsistent solutions are discarded and the system processor navigates the UAV in position for refueling using the remaining relative navigation solutions. <CIT> discloses a system for generating and utilizing a look-up mechanism consisting of one or more phase difference error maps, tables and/or mathematical models, for calculating the respective maps, tables and/or models by placing a short baseline or ultra-short baseline antenna array in a known location and known orientation, for determining angles of incidence of incoming GNSS satellite signals with respect to the antenna array and calculating expected carrier phase differences between respective pairs of antennas, for calculating measured carrier phase differences between the respective pairs of antennas, and for determining carrier phase difference errors using the expected and measured carrier phase differences. The carrier phase difference errors are then recorded in the look-up mechanism, with the maps and, as appropriate, look-up tables for the respective pairs of antennas being indexed by angles of incidence. Thereafter, the system utilizes the lookup mechanism when determining the unknown orientation of the antenna structure. For respective pairs of antennas, the system enters the look-up mechanism based on angles of incidence determined from a calculated orientation, and uses the retrieved values in the calculation of a corrected orientation, to compensate for phase distortion.

In accordance with an aspect of the present invention, a method is provided for monitoring carrier phase anomalies in a range finding system. A relative carrier phase between first and second antennas is predicted as a function of a relative position between the two antennas. A relative carrier phase between the first and second receivers is measured based upon at least one transmitted signal received at each of the first and second antennas. An anomaly detection metric is calculated as a difference between the measured relative carrier phase and the predicted relative carrier phase. It is then determined if an anomaly is present according to the anomaly detection metric.

In accordance with another aspect of the present invention, a system includes a first antenna configured to receive a signal from a transmitter and a second antenna configured to receive the signal from the transmitter, with the second antenna being separated from the first antenna by a baseline. A signal processor is configured to calculate a measured relative carrier phase between the first antenna and the second antenna according to the received signal. A relative carrier phase estimator is configured to estimate a predicted relative carrier phase between the first antenna and the second antenna according to the baseline between the first antenna and the second antenna. An anomaly detection component is configured to determine if an anomaly is present according to an anomaly detection metric. The anomaly detection metric is determined as a function of a difference between the measured relative carrier phase and the predicted relative carrier phase.

In accordance with still another aspect of the present invention, a global navigation satellite system includes a first receiver configured to receive signals from a plurality of GNSS satellites and a second receiver configured to receive signals from the plurality of GNSS satellites, with respective antennas of the first and second receivers being separated by a known baseline. A signal processor is configured to calculate a double differenced carrier phase between the first receiver and the second receiver according to the received GNSS satellite signals. A relative carrier phase estimator is configured to estimate a predicted relative carrier phase between the first receiver and the second receiver according to the baseline between the first antenna and the second antenna. An anomaly detection component is configured to determine that an anomaly is present if a difference between the measured relative carrier phase and the predicted relative carrier phase exceeds a predetermined threshold value.

The features, objects, and advantages of the invention will become more apparent from the detailed description set forth below when taken in conjunction with the drawings, wherein:.

In accordance with an aspect of the present invention, systems and methods are provided for anomaly detection in range finding systems. The system deals with detection of measurement anomalies by using knowledge of the relative distance between the receivers to predict some aspects of the expected measurements. The systems and methods described herein identify measurement anomalies by applying a known baseline constraint to the incoming carrier phase measurements between two antennas to predict the measurements and detect deviation from the predicted measurements. The incoming relative carrier phase measurements are predicted using precise knowledge of the position difference between these two antennas, either in space or in time. This measurement prediction provides a reference for detecting carrier phase anomalies affecting either of the receivers in the baseline. This technique is not dependent on statistically resolving carrier cycle counts since they are directly computed at each time epoch. Precise knowledge of the baseline can either come from a priori knowledge of a rigid baseline (e.g., antenna self-calibration survey) or from a secondary measurement of the flexible antenna baseline (e.g., laser ranging).

Carrier phase measurements are very precise due to a receiver's ability to track the carrier within a small fraction of its wavelength. Carrier phase measurements are used in many different domains including global navigation satellite systems (GNSS) such as the Global Positioning System (GPS) interferometry and Very Long Baseline Interferometry (VLBI) radar processing. The measurement consumer in each domain desires an assessment of the measurement accuracy and reliability. Systems and methods in accordance with an aspect of the present invention provide an algorithm for receiver-level anomaly detection in any domain that uses carrier phase interferometry by comparing the received measurements with synthetic measurement predictions. In addition, this technique can be used to provide geometrically constrained corrections for post-correlation digital beam forming by predicting the differential carrier phase measurements produced by a controlled reception pattern antenna (CRPA) in conjunction with the inertial attitude and heading measurements.

<FIG> illustrates one example of a range finding system <NUM> utilizing anomaly detection in accordance with an aspect of the present invention. The range finding system <NUM> includes at least two antenna locations <NUM> and <NUM> associated with at least one antenna configured to receive signals from one or more transmitters. In general, the system will have multiple antennas, but it will be appreciated that the antenna locations <NUM> and <NUM> can represent multiple measurements at a single antenna made at two different times on a moving platform. Where multiple antennas are present, each antenna will generally be associated with a specific receiver platform, but it will be appreciated that in some applications, a single platform may have multiple, and even redundant, antennas to allow for integrity monitoring of the signals received at the antennas. Each of these signals will generally contain a structured or pseudo-random code that can be used for determining a time-of-flight for the signal. The received signals are processed at an associated signal processor <NUM> that calculates a measured relative carrier phase between a given pair of the at least two antenna locations <NUM> and <NUM>. In one implementation, the measured relative carrier phase is determined as a double differenced relative carrier phase.

In accordance with an aspect of the present invention, the given pair of the at least two antenna locations <NUM> and <NUM> can be separated by a known baseline <NUM>. In one implementation, the baseline <NUM> is fixed, such that a measurement prior to operation of the system can be used. The carrier phase ambiguity can be resolved using the fixed baseline constraint. For example, the baseline length can be surveyed in a body frame associated with the system <NUM> using external sensors and then transformed from body coordinate frame to navigation coordinates. If the platform for the system is nominally a two-dimensional platform such as a car or train, only a heading is required from an external sensor, such as a magnetometer, for this transformation. For a three-dimensional platform such as a boat or aircraft, a leveled inertial measurement can be added to estimate the roll and pitch of the platform to allow for the shift in the orientation of the baseline relative to the navigation frame of reference to be tracked. As long as the external sensors provide an accurate enough orientation to predict the rotated baseline within one-half of a wavelength of the range finding system <NUM>, the ambiguity can be deterministically resolved in a single epoch.

It will be appreciated that the baseline <NUM> can be flexible, that is, variable, and in these implementations, the baseline is monitored on a periodic or continuous basis by an external measurement device (not shown). For example, the two antenna locations <NUM> and <NUM> can be on different mobile platforms or located on a portion of a single platform that flexes with movement, such that their relative positions are not fixed. In one implementation, laser ranging can be used to monitor the flexible baseline. A relative carrier phase (RCP) estimator <NUM> is configured to calculate a predicted relative carrier phase from the known baseline. In one implementation, the predictive relative carrier phase is calculated as a function of the known baseline and a representation of a line of sight between the one or more transmitters and at least one of a first antenna location of the given pair <NUM>, a second antenna location of the pair <NUM>, and a point located on the baseline <NUM> between the two antenna locations.

Each of the measured carrier phase and the predicted relative carrier phase are provided to an anomaly detection component <NUM>. The anomaly detection component <NUM> determines if a measurement anomaly is present according to an anomaly detection metric determined as a function of a difference between the predicted relative carrier phase and the measured relative carrier phase. For example, the anomaly detection component <NUM> can provide the calculated anomaly detection metric to as a feature to an expert system, for example, a regression model, an artificial neural network classifier, or a rule-based expert system, to determine if an anomaly is present. It will be appreciated that multiple anomaly detection metrics can be accumulated over a predetermined period of time, such that an expert system can utilize a time series of metrics as classification features. The anomaly detection component <NUM> compares the difference between the measured relative carrier phase and the predicted relative carrier phase to a threshold value determine if a measurement anomaly is present. For example, the threshold can be equal to a quarter of a characteristic wavelength associated with a carrier of the received signals. If the difference exceeds the threshold, an anomaly flag can be triggered to indicate that a measurement anomaly is present. For example, a measurement anomaly can indicate a tracking error associated with one of the antennas or the presence of fake signals as might be caused by spoofing or meaconing.

<FIG> illustrates one implementation of a global navigation satellite system (GNSS) <NUM> utilizing anomaly detection in accordance with an aspect of the present invention. In the illustrated implementation, a plurality of receivers <NUM>-<NUM> detect a navigation signal provided by one or more GNSS satellites. At each receiver <NUM>-<NUM>, the incoming satellite signals are received by one or more elements on a multi-element GPS antenna <NUM>-<NUM> and converted into usable signals. For example, the receivers <NUM>-<NUM> can include a multi-channel RF front-end that downconverts the received signal to baseband. The downconverted signals are then digitized and provided to a plurality of signal extractors <NUM>-<NUM>. In the illustrated implementation, the signal extractors <NUM>-<NUM> can include correlators configured to search the Doppler and delay correlation space for the strongest correlation energy indicating the presence of an incoming signal. The correlators can be setup to provide localized correlation values at points surrounding the acquired signals which then allows signal tracking. Once the signal is located by the correlators, range finding information is extracted from the signal, making it possible to determine a time of transit of the signal, and thus a psuedorange to the transmitter from each receiver <NUM>-<NUM>.

The extracted range finding information can include a code pseudorange, which is the "distance" between the transmitter at some transmit time and the receiver at some receive time. Because the transmit time and the receive time are different, it is impossible to measure the true range between the satellite and the receiver. A phase psuedorange is based on the carrier phase of the signal and does not require the actual information being transmitted. In the illustrated implementation, the carrier phase is used instead of the code or phase psuedorange. To determine the carrier phase (i.e., accumulated Doppler range), a fractional beat phase of the received signal with a signal from from a local oscillator having known properties can be measured and converted into the range domain by scaling the measured beat with the wavelength.

A system control <NUM> includes a relative carrier phase (RCP) calculation component <NUM> that determines a relative phase between the two receivers from the determined phase measurements. It will be appreciated that the system control <NUM> can be located at one of the receivers (e.g., <NUM>), distributed among the plurality of receivers <NUM>-<NUM>, or located remotely. The illustrated system <NUM> uses differenced phase processing to determine the relative phase. Differenced phase processing generally uses measurements from two or more receivers at arbitrary positions to cancel common errors via carrier phase interferometry techniques. The illustrated system <NUM> uses double differenced processing to form the interferometric observations. In double difference processing, single differences are formed by determining differences between observations from two separate receivers to a single satellite. Taking the difference between two single differences for a specific receiver pair gives the carrier phase double difference, which can be used to determine the relative carrier phase between the pair of receivers.

The system control <NUM> can further include a relative carrier phase predictor <NUM> that calculates a predicted relative carrier phase between two receivers according to a known baseline between the receivers. In one implementation, the predicted relative carrier phase is calculated as a product of a line of sight matrix, representing a line of sight between the transmitters and at least one point on the baseline, and a position vector representing the known baseline (e.g., a relative position of the two receivers). It will be appreciated that the line of sight matrix generally represents a direction of one or more transmitters from one or both of the receivers in the pair defining the baseline. It will be appreciated that the baseline between two receivers can be rigid and measured during a configuration of the system to provide the known baseline. In the illustrated implementation, however, a flexible (i.e., variable) baseline is assumed, and the system control <NUM> can be operatively connected to a baseline measurement component <NUM> configured to dynamically measure the baseline. For example, the baseline measurement component <NUM> can include a laser rangefinder configured to measure the distance between the two receivers, specifically, between the antennas associated with the receivers.

A calibration can be performed to determine the baseline vector and its orientation in space within a body-referenced coordinate frame used by an inertial navigation system (INS) <NUM>. The INS can be used to continuously provide the dynamic relationship between the body and navigation frames and thus the ability to predict the relative carrier phase measurements. The coordinate frame transform can be accomplished using two direction cosines matrices. A first matrix provides a static calibration which relates a survey frame to the body frame, while the second matrix provides an on-the-fly conversion which relates the static body coordinate frame to the dynamic navigation frame, for example, using the relationship determined at the INS <NUM>. Accordingly, a known or measured baseline in the body frame can be represented in the navigation frame to allow for prediction of the relative carrier phase.

It will be appreciated that the measured carrier phase can have a degree of ambiguity, for example, in the integer number of wavelengths between two phase measurements. This carrier phase ambiguity can be resolved using a known rigid baseline constraint. This involves surveying the baseline length in the body frame and then transforming it from body to navigation coordinates using external sensors. If the platform is nominally a two-dimensional platform such as a car or a train, only a heading is required from an external sensor such as a magnetometer. For a three-dimensional platform, such as a boat or an aircraft, a leveled IMU can be added to estimate the roll and pitch of the platform. As long as the external sensors provide accurate enough orientation to predict the rotated baseline within one-half of a wavelength, the ambiguity can be deterministically resolved in a single epoch.

Consider, for example, a 2D rigid baseline of length one meter and a magnetometer with an accuracy of ±<NUM> degree. For this case, the magnetometer can be used to predict the baseline in navigation coordinates with an accuracy of <NUM>. A longer baseline amplifies the position prediction error for a given magnetometer error. For a two meter baseline and the same magnetometer, the position prediction accuracy would be <NUM>. Both cases are within half of the <NUM> L1 GPS wavelength.

Accordingly, a raw widelane quantity, WLraw, can be computed as: <MAT> where SDL1 is a single differenced phase measurement on the L1 carrier, where SDL2 is a single differenced phase measurement on the L2 carrier, where DDL1, raw is a raw double differenced phase measurement on the L1 carrier, where DDL2, raw, is a raw double differenced phase measurement on the L2 carrier, λL1 is a wavelength of the L1 carrier, λL2 is a wavelength of the L2 carrier, and λWL is the wide lane wavelength.

The body-frame baseline and heading, DDest, can be parameterized as: <MAT> where bn is the baseline in a navigational frame, H is the heading, bb is the baseline in a body frame, and Cbn is a rotation matrix representing the alignment of the body in the navigation frame.

The narrowlane ambiguity, NWL, can be determined as a difference between the raw widelane ambiguity and the body frame baseline and heading, such that NWL=round(WLraw-DDest). A final widelane quantity, WL, can be computed as WLraw - NWL* λWL. A handover, HO, can be computed as a moving average filter, such that HO = wavg(DDL1,raw-WL), with an L1 ambiguity, NL1, computed as NL1=round(HO/λL1). An L2 ambiguity is determined as a difference between the L1 ambiguity and the narrowlane ambiguity. From these values, single frequency measurement, DDL1 and DDL2, can be determined as: <MAT>.

Once a carrier phase between at least two receivers has been measured and a predicted relative carrier phase has been calculated, both values are provided to an anomaly detection component <NUM>. The anomaly detection component <NUM> determines if a measurement anomaly is present from a difference between the predicted relative carrier phase and the measured relative carrier phase. The anomaly detection component <NUM> compares a difference between the measured relative carrier phase and the predicted relative carrier phase to a threshold value determine if a measurement anomaly is present. For example, the threshold can be equal to a quarter of a characteristic wavelength associated with a carrier of the received signals. If the difference exceeds the threshold, an anomaly flag can be triggered to indicate that a measurement anomaly is present. For example, a measurement anomaly can indicate a tracking error associated with one of the antennas or the presence of fake signals as might be caused by spoofing or meaconing.

Many interferometry systems have spatially or temporally separated antennas (or elements) which could employ the techniques for anomaly detection described herein. For example, many anti-jam navigation systems use a controlled reception pattern antenna or enhanced jamming protection. <FIG> illustrates a controlled reception pattern antenna <NUM> that could utilize an anomaly detection system in accordance with an aspect of the present invention. The controlled reception pattern antenna <NUM> comprises a plurality of antenna nodes <NUM>-<NUM> maintained at constant relative positions. Accordingly, respective baselines <NUM>-<NUM> between a first antenna node <NUM> and neighboring antenna nodes <NUM>-<NUM> are rigid, and can be measured, for example, during an antenna self-calibration survey. In the illustrated implementation, these rigid baselines are measured in a body-referenced coordinate frame through a static survey and must be dynamically converted to a navigation coordinate frame to account for movement and rotation of the platform before they can be used for measurement prediction. Measurement anomalies can be detected for the CRPA when the phase measurements are processed individually from each antenna element, and the measurements do not match the predicted phase measurements.

Another example antenna arrangement <NUM> is shown in <FIG>, in which the anomaly monitoring system monitors a rigid baseline <NUM> between redundant antennas <NUM> and <NUM> to validate nodal measurements which are constituents of a flexible baseline (e.g., <NUM> or <NUM>) between one of the redundant antennas (e.g., <NUM> or <NUM>) and a third antenna <NUM>. Essentially, the addition of a redundant antenna (e.g., <NUM>) creates a rigid baseline <NUM> with one of the antennas <NUM> in a pair of antennas <NUM> and <NUM> needed for an application. This rigid baseline <NUM> allows for a more accurate prediction of the relative carrier phase, and accordingly, for more accurate anomaly monitoring. Since many sources of error would affect all local antennas, the more accurate anomaly monitoring over the rigid baseline <NUM> can be used to ensure the integrity of the entire array <NUM>. Redundant antennas might be used, for example, on an airborne refueling platform to facilitate the use of an anomaly monitoring system as an input to an integrity monitor. A similar configuration could be used for very long baseline interferometry (VLBI) radars, in which the radar aperture is extended to include multiple antennas and the radar measurement is compared against a prediction drawn from redundant antennas.

While the example of <FIG> utilizes multiple antennas and multiple receivers, the same techniques can also be used temporally, with the antenna baseline formed at two or more discrete times from the same receiver. The temporal baseline can be constrained by an external observation of displacement (e.g., inertial measurement unit or odometer) and thereby provide a means to predict the expected carrier phase measurement and form a detection metric.

In the examples of <FIG>, the anomaly detector can detect measurement errors whose magnitude is a small fraction of the measurement wavelength as long as the anomaly is larger than the measurement noise. Anomalies include events at the receiver-level, such as tracking errors, or at the signal level, such as fake signals like spoofing or meaconing. This technique is not limited by the correctness of ambiguity resolution, or error sources such as correlated noise, multipath, or cycle slips. In fact, an anomaly detection system in accordance with an aspect of the present invention is sensitive enough to detect these error sources.

In view of the foregoing structural and functional features described above, an example method will be better appreciated with reference to <FIG>. While, for purposes of simplicity of explanation, the method of <FIG> is shown and described as executing serially, it is to be understood and appreciated that the present invention is not limited by the illustrated order, as some actions could, in other examples, occur in different orders from that shown and described herein or could occur concurrently.

<FIG> illustrates a method <NUM> for monitoring carrier phase anomalies in a range finding system in accordance with an aspect of the present invention. At <NUM>, a relative carrier phase between first and second antennas is predicted as a function of a relative position between the two antennas. It will be appreciated that the relative position can be known from a calibration of the range finding system and simply stored as a parameter in a system control. Alternatively, the relative position between the two antennas can be periodically determined, for example, via laser range finding or another appropriate means for tracking the relative position of two objects. In general, the relative position between the two antennas is determined in a body-referenced coordinate frame associated with the range finding system and translated to a navigation coordinate frame via a coordinate transform. In one implementation, the relative carrier phase is predicted as a function of the relative position between the two antennas and a known position of a plurality of transmitters in the range finding system. For example, the predicted relative carrier phase can be calculated as a product of a line of sight matrix, representing the relative position of the plurality of transmitters and at least one point associated with a baseline between the two antennas, and a vector representing the relative position of the two antennas.

At <NUM>, a relative carrier phase between the first and second antennas is measured based upon at least one transmitted signal received at each of the first and second antennas. In one implementation, a double differenced carrier phase can be calculated for the two antennas using signals from two transmitters having known locations relative to the antennas. At <NUM>, an anomaly detection metric is determined as a function of a difference between the measured relative carrier phase and the predicted relative carrier phase. In one implementation, the anomaly detection metric is a linear function of the difference between the measured relative carrier phase and the predicted relative carrier phase, but it will be appreciated that, depending on the analysis means used to detect the anomaly, that non-linear functions of this difference may be useful.

At <NUM>, it is determined if an anomaly is present according to the anomaly detection metric. An anomaly is determined to be present if the anomaly detection metric exceeds a predetermined threshold value, such as one-quarter of a wavelength associated with one of the at least one transmitted signal. In another implementation, a rule-based expert system is provided with a time series of calculated anomaly detection metrics to determine a likelihood that an anomaly is present. Once a measurement anomaly is detected, it can be flagged and reported to an operator to allow for appropriate adjustment to the range finding system.

Claim 1:
A method for monitoring carrier phase anomalies in a range finding system (<NUM>) comprising:
predicting, by an relative carrier phase estimator (<NUM>), a relative carrier phase between locations of a first and a second antenna (<NUM>, <NUM>) as a function of a relative position between the locations of the two antennas (<NUM>, <NUM>), where the first and the second antennas (<NUM>, <NUM>) are each configured to receive a signal from a transmitter and a baseline between the locations of the two antennas (<NUM>, <NUM>) is known;
measuring, by signal processor (<NUM>), a relative carrier phase between the locations of the first and second antennas (<NUM>, <NUM>) based upon at least one transmitted signal received at each of the locations of the first and second antennas (<NUM>, <NUM>);
calculating, by an anomaly detection component (<NUM>), an anomaly detection metric as a function of a difference between the measured relative carrier phase and the predicted relative carrier phase;
determining, by the anomaly detection component (<NUM>), if an anomaly, comprising one of a tracking error at the antennas and an introduction of false signals via spoofing or meaconing, is present according to the anomaly detection metric, by determining if the anomaly detection metric exceeds a predetermined threshold value; and
indicating, by the anomaly detection component (<NUM>), that an anomaly is present, if the predetermined threshold value is exceeded, to allow adjustment to the range finding system; wherein
the predetermined threshold value is one-quarter of a wavelength associated with the transmitted signal.