Abstract: A system for detection of human or vehicle activity comprising at least one sensor adapted to generate a signal and at least one processor operating to denoise the signal; generate an autocorrelation of the signal; partition the signal into a predetermined number of overlapping segments to form a time series of data; generate symbols for the overlapping segments; compare the pattern of generated symbols with known predetermined patterns of symbols representing human or vehicular activity; determine whether a threshold probability is exceeded which attributes the data signal to human or vehicular activity; analyze the patterns presented in the data signal by transforming the patterns of symbols into states; determine the transitions between states; and classify the signal as to being attributable to human or vehicular activity based upon the transitions between states. A method of detection and classification of sensor data signals via detecting patterns using time series analysis.

Abstract: A system and method for identifying the location of gunfire from a moving object in which at least two spaced apart microphones are positioned on the moving object. The output from the microphones is decomposed into intrinsic mode functions by using empirical mode decomposition. A transient pulse is then identified in the intrinsic mode function representative of the gunfire. The location of the origin of the gunfire is then determined from the transient pulses through multilateration using time difference of arrival of the transient pulses by the microphones.

Abstract: A system for detection of human or vehicle activity comprising at least one sensor adapted to generate a signal and at least one processor operating to denoise the signal; generate an autocorrelation of the signal; partition the signal into a predetermined number of overlapping segments to form a time series of data; generate symbols for the overlapping segments; compare the pattern of generated symbols with known predetermined patterns of symbols representing human or vehicular activity; determine whether a threshold probability is exceeded which attributes the data signal to human or vehicular activity; analyze the patterns presented in the data signal by transforming the patterns of symbols into states; determine the transitions between states; and classify the signal as to being attributable to human or vehicular activity based upon the transitions between states. A method of detection and classification of sensor data signals via detecting patterns using time series analysis.

Abstract: A system and method for identifying the location of gunfire from a moving object in which at least two spaced apart microphones are positioned on the moving object. The output from the microphones is decomposed into intrinsic mode functions by using empirical mode decomposition. A transient pulse is then identified in the intrinsic mode function representative of the gunfire. The location of the origin of the gunfire is then determined from the transient pulses through multilateration using time difference of arrival of the transient pulses by the microphones.

Abstract: A method and system for detecting targets comprising at least one first receiver for receiving radiation, the radiation comprises beams of radiation spaced horizontally; at least one second receiver for receiving radiation, the radiation comprises beams of radiation spaced horizontally and vertically such that the beams of radiation received by the second receiver travel through different predetermined heights from the horizontal plane; at least one processor for receiving data from the first and second receivers, the at least one receiver operating to locate a target passing in the vicinity of the first and second receivers and determine the height of the target based upon the recordation of certain of the beams at a predetermined heights relative to the horizontal plane and the width of a target based upon the horizontal spacing of the beams.

Abstract: A method and system for detecting targets comprising at least one first receiver for receiving radiation, the radiation comprises beams of radiation spaced horizontally; at least one second receiver for receiving radiation, the radiation comprises beams of radiation spaced horizontally and vertically such that the beams of radiation received by the second receiver travel through different predetermined heights from the horizontal plane; at least one processor for receiving data from the first and second receivers, the at least one receiver operating to locate a target passing in the vicinity of the first and second receivers and determine the height of the target based upon the recordation of certain of the beams at a predetermined heights relative to the horizontal plane and the width of a target based upon the horizontal spacing of the beams.

Abstract: An apparatus and method of sniper localization includes an internal clock; an acoustic sensor positioned in a known location and detecting pressure waves; a first processor determining the trajectory of the supersonic projectile, where the first processor includes a shock wave threshold detector receiving time series information and recording arrival times of shock wave components of the pressure waves; a blast threshold detector receiving the time series information and recording arrival times and amplitude information of blast wave components of the pressure waves; a discrimination processor discriminating between a blast wave, a shock wave, or neither, and storing arrival times of each of the potential blast wave components classified as the blast wave; and a localization estimation processor calculating an estimated trajectory of the projectile based on the blast wave and the shock wave arrival times and calculating an estimated firing position of the projectile.

Abstract: Methods and apparatuses for locating a sensor node are disclosed. A representative apparatus, among others, includes a processing unit that receives sensor node data and object trajectory information data for an object. The sensor node data is related to the object's trajectory, and a data point in the object trajectory information data comprises a time stamp and the coordinates of a position. The position corresponds the location of the object at the given time. The processing unit is adapted to correlate at least a portion of the sensor node data with at least a portion of the object trajectory information data to determine an absolute position of the sensor node.

Abstract: An apparatus and method of sniper localization includes an internal clock; an acoustic sensor positioned in a known location and detecting pressure waves; a first processor determining the trajectory of the supersonic projectile, where the first processor includes a shock wave threshold detector receiving time series information and recording arrival times of shock wave components of the pressure waves; a blast threshold detector receiving the time series information and recording arrival times and amplitude information of blast wave components of the pressure waves; a discrimination processor discriminating between a blast wave, a shock wave, or neither, and storing arrival times of each of the potential blast wave components classified as the blast wave; and a localization estimation processor calculating an estimated trajectory of the projectile based on the blast wave and the shock wave arrival times and calculating an estimated firing position of the projectile.

Abstract: Methods and apparatuses for locating a sensor node are disclosed. A representative apparatus, among others, includes a processing unit that receives sensor node data and object trajectory information data for an object. The sensor node data is related to the object's trajectory, and a data point in the object trajectory information data comprises a time stamp and the coordinates of a position. The position corresponds the location of the object at the given time. The processing unit is adapted to correlate at least a portion of the sensor node data with at least a portion of the object trajectory information data to determine an absolute position of the sensor node.

Abstract: A built-in test system for analog or mixed signal circuits comprises a discretizer for discretizing analog test signals monitored at various node points of the circuit under test into suitable discrete values. The discrete values are compared with a reference signature in an analog signature generator to determine if a fault is likely. Since analog signature generators use multilevel data, the computations are performed in Galois field GF(p), where p is the radix. The analog signature generator is constructed using current-mode shift registers, signal discretizers, signal level shifters, mod-p adders, subtractors and multipliers.

Abstract: A built-in self test method and circuit identifies a faulty integrated ciit chip in a multichip module. The built-in self test method first applies a test pattern to a multichip module having a plurality of integrated circuit chips and to a reference signal generator, generates a first and second reference signal representing test responses for a fault free multichip module, compresses the outputs from the multichip module into a first and second bit using a first and second linear space compressor, uses exclusive OR logic to combine the first bit with the first reference signal to produce a first fault detection output and to combine the second bit with the second reference signal to produce a second fault detection output, stores the first and second fault detection outputs in a pair of N-bit shift registers; compares the stored outputs to detect a fault condition, and applies a series of recursive logic operations to identify the faulty integrated circuit chip in the multichip module.