Raytheon Company

Eran Marcus

Adam Hodge Greenberg

Brian F Boland

Vitaliy M Kaganovich

Robert D Stultz

Joseph C Marron

David U Fluckiger

Arthur M Newman

Louis Zellinger

Derek M Hendry

Nathaniel Wyckoff

An apparatus, and method of operating the same processes of LADAR data including iterating back and forth between target detection in a 2-D array having range and range rate dimension, and a 4-D array having azimuth, azimuthal velocity, elevation, & elevation velocity dimensions. The apparatus includes a receiver and a processor arranged to generate photo events including target signal photo events and background photo events, transform the photo events into the 2-D target tracking array including range and range-rate parameters and tag photo events determined to be 2-D target signal photo events. The processor transforms tagged photo events into the 4-D target and tags photo events determined to be 4-D target signal photo events.

Six dimensional tracking of sparse LADAR data

System and method for generating Pulse Position Modulated (PPM) lidar waveforms generating Pulse Position Modulated (PPM) waveforms in a lidar includes: a) creating a modulation pool, based on a maximum nominal pulse repetition frequency (PRF); b) eliminating bad modulation levels from the modulation pool to generate a good modulation pool; c) selecting a modulation level from the good modulation pool to generate a PPM code element; d) repeating steps b and c N times to generate an N-element PPM code, wherein the PPM code is PRF independent; e) selecting a PRF less than the maximum nominal PRF; f) generating a PPM waveform by applying the N-element PPM code to the selected PRF; and g) transmitting the PPM waveform by the lidar toward a target to determine a range to the target.

System and method for generating PPM waveforms

A laser transmitter including a waveform controller arranged to generate a waveform script having at least one of a pulse repetition frequency setting, a pulse duration setting, and a pulse amplitude pre-warp setting. The transmitter also includes an optical waveform generator arranged to: i) receive the waveform script, ii) generate pre-warped signal pulses based on the waveform script to compensate for gain distortion effects of a laser power amplifier, and iii) output the pre-warped signal pulses. The laser power amplifier is arranged to: i) receive the pre-warped signal pulses, ii) receive a continuous wave signal, and iii) output amplified signal pulses that maintain a substantially constant drive intensity at the input of a non-linear wavelength converter. The non-linear wavelength converter is arranged to receive the amplified signal pulses and emit wavelength-converted pulses.

Systems and methods for control of waveform-agile laser transmitter

Lidar and method for generating repeatable PPM waveforms to determine a range to a target include: a processor for a) creating a modulation pool, based on a maximum nominal PRF and a specified final PPM code length of N; b) obtaining a seed code; c) eliminating bad modulation levels from the modulation pool to generate a good modulation pool, d) selecting a modulation level from the good modulation pool; e) concatenating the selected modulation level to the seed code to generate an i-element modulation sequence; f) repeating steps c to e N times to generate an N-element modulation sequence; g) selecting a PRF less than the maximum nominal PRF; and h) generating a repeatable PPM waveform by applying the N-element modulation sequence to the selected PRF.

System and method for generating repeatable PPM waveforms

A laser detection and ranging system and method for operating thereof. In some embodiments, the method includes: transmitting a plurality of laser pulses, each at a respective one of a plurality of pulse transmission times; detecting a plurality of return pulses, each at a respective one of a plurality of return pulse times; and estimating a range or a range rate of a target based on the pulse transmission times and the return pulse times. Each of the pulse transmission times may be offset from a corresponding nominal pulse transmission time by a respective pulse position modulation offset, the nominal pulse transmission times being uniformly spaced with a period corresponding to a pulse repetition frequency, the pulse repetition frequency being greater than 500 kHz.

High pulse repetition frequency lidar

A lidar for generating long PPM waveforms receives an initial PPM code element including a number of code elements and a desired maximum sidelobe height; b) generates a two-column lookup table; c) selects a candidate modulation level; d) compares the values of the number of times a code element difference has been observed in the initial PPM code element from the lookup table against the desired maximum sidelobe height; e when a value of the number of times exceeds the desired maximum sidelobe height, discards the selected candidate modulation level, decrements corresponding values in the lookup table and repeats steps c to d; f otherwise, appends the selected candidate modulation level to the end of the initial PPM code element to update the initial PPM code element, and repeats steps c to f N times to generate a PPM waveform of length N.

System and method for generating very long PPM waveforms

A target acquisition system includes a transmitter configured to emit a plurality of pulses at a plurality of transmit times toward a target, a receiver configured to detect a plurality of photon arrival events at a plurality of receive times, and a processor configured to determine a range of the target and a range-rate of the target by identifying a subset of the receive times and a subset of the transmit times, generating scaled transmit times based on the subset of the transmit times and a plurality of trial target velocities relative to the receiver, cross-correlating the scaled transmit times and the subset of the received times to generate a plurality of cross-correlation power values, and calculating the range and the range-rate of the target based on the plurality of cross-correlation power values.

System and method for determining range-rate and range extent of a target

A transmitter for communication-less bistatic ranging includes a photon emitter configured to emit a plurality of photons at particular times in a pointing direction, and a processor configured to identify a particular sub-code of a plurality of sub-codes based on a dynamic state of the transmitter, each one of the plurality of sub-codes including a portion of a long optimal ranging code, generate a plurality of encoded pulse timings by dithering pulse timings from a nominal repetition frequency based on the particular sub-code, and control the photon emitter to emit the plurality of photons at the plurality of encoded pulse timings.

Communication-less bistatic ranging

A method for operating a laser detection and ranging system. In some embodiments, the method includes transmitting a plurality of laser pulses, each at a respective one of a plurality of pulse transmission times; detecting a plurality of return pulses, each at a respective one of a plurality of return pulse times; forming a first time difference, the first time difference being the difference between a first return pulse time of the plurality of return pulse times and a first pulse transmission time of the plurality of pulse transmission times; and incrementing a first element of a first array, the first element of the first array having an index based on the first time difference.

System and method for calculating a binary cross-correlation

A measured photo-event array is converted from two spatial coordinates and one temporal coordinate into three spatial coordinates for real-time imaging. Laser light pulses illuminate at least one object, and a Geiger-mode avalanche photodiode array receives photons from laser light reflected off the object. For each pulse of the laser light, the GMAPD outputs a first array of photo-events representative of reflected photons. A three-dimensional (3D) Gaussian distribution kernel arranged as a list of array locations to be processed and weight list(s) are provided. The weight list(s) specify an amount array values are scaled based on the Gaussian distribution or photon arrival time. A graphics processing unit arranges the first array of measured photo-events as a list, convolves the Gaussian displacement list with the list of measured photo-events to produce a convolution output, and applies weights from the weight list(s) to the values to produce a density point cloud.

Real-time image formation from Geiger-mode LADAR

A system and method for forming a range estimate for a target with a laser detection and ranging system. The system includes a laser transmitter and an array detector. The method includes: transmitting a plurality of laser pulses; for each transmitted laser pulse: detecting, with the array detector, a plurality of ladar return photons from the laser pulse, each detection producing an electrical pulse; identifying, for each of the electrical pulses, a time bin of a plurality of time bins corresponding to the laser pulse, within which the electrical pulse was produced; forming a one dimensional range histogram array having, for each of a subset of the plurality of bins, an element with a value equal to the number of electrical pulses produced in the array detector during a time interval corresponding to the bin; and forming an estimated range rate for the target.

Ladar range estimate with range rate compensation

A system and method for forming an image of a target with a laser detection and ranging system. The system includes a laser transmitter and an array detector. The method includes transmitting a sequence of laser pulses; forming a plurality of point clouds, each point cloud corresponding to a respective transmitted laser pulse, each point in the point cloud corresponding to a point on a surface of the target; grouping the plurality of point clouds into a plurality of point cloud groups according to a contiguous subset of the sequence of laser pulses; forming a plurality of average point clouds, each of the average point clouds being the average of a respective group of the plurality of point cloud groups; and forming a first estimate of a six-dimensional velocity of the target, including three translational velocity components and three angular velocity components, from the plurality of average point clouds.

Motion compensation for dynamic imaging

A method for computing a cross-correlation between a first sequence and a second sequence includes: generating a first index vector based on the first sequence, the first index vector including a plurality of first elements, the first index vector excluding indices of zero valued elements of the first sequence; generating a second index vector based on the second sequence, the second index vector including a plurality of second elements, the second index vector excluding indices of zero valued elements of the second sequence; computing, on a processor, a plurality of pairwise differences between each of first elements of the first index vector and each of the second elements of the second index vector; and binning, on the processor, the plurality of pairwise differences to generate the cross-correlation of the first sequence and the second sequence.

Computing cross-correlations for sparse data

A target recognition system and method. The inventive method includes the steps of first receiving an image of a scene within which a target may be included and second using constrained image segmentation as a basis for target recognition. In the specific embodiment, the segmentation is variable and derived from target geometry models. The constrained image segmentation is adapted to use target geometry models to derive alternative image segmentation hypotheses. The hypotheses are verified using a novel hierarchical adaptive region model matcher. In the best mode, the hierarchical adaptive region model matcher is fully hierarchical and includes the steps of receiving an image and a hypothesis with respect to a target in the image. In the illustrative embodiment, the hypothesis contains the type, location, and/or orientation of a hypothesized target in the image. The hypothesis is received by a model tree generator. A target model library provides a plurality of computer generated target models. The model tree generator retrieves a model from the library based on a hypothesized target type and renders a model tree therefrom that represents the appearance of a hypothesized target at a hypothesized location and orientation. In the illustrative embodiment, the verification model further includes a search manager adapted to receive a model tree from the model tree generator. A feature extractor is included along with a segmentation evaluator. The segmentation evaluator is coupled to receive image features from the feature extractor. The segmentation evaluator is adapted to output a segmentation score to the search manager with respect to a specified set of segmentation labels based on a supplied set of image features for an active node.

Growing community of inventors

Culver City, CA, United States of America

Eran Marcus