In 2019, the World Health Organization stated that globally, approximately 2.2 billion people live with some form of vision impairment. Visual impairment limits the ability to perform everyday tasks and adversely affects the ability to interact with the surrounding world, thus discouraging individuals navigating unpredictable and unknown environments. The present invention is a method and a system to define and develop a smart navigation intelligent cane (i-Cane) that enables a visually impaired person to navigate his or her environment. The method and the system detects objects along the path of the visually impaired person, measures the distance of the objects from the person, identifies the objects, uses speech to alert the person of the approaching objects, the type of objects obstructing the path, and the distance between the objects and the person.

A method classifies dynamic or static objects in a surrounding area with a control device. Sound echoes are generated by at least one sensor over a defined time period. The sound echoes are emitted into the surrounding area, and are detected by the at least one sensor in order to acquire measurement data. The measurement data of the at least one sensor are received by the control device. The received measurement data are recorded in a two-dimensional array. At least one echo trace is extracted from the array. A relative speed of the detected sound echoes with respect to the at least one sensor is determined using a derivative over time of the measurement data of the array. The at least one echo trace is classified based on the determined relative speed.

A method classifies dynamic or static objects in a surrounding area with a control device. Sound echoes are generated by at least one sensor over a defined time period. The sound echoes are emitted into the surrounding area, and are detected by the at least one sensor in order to acquire measurement data. The measurement data of the at least one sensor are received by the control device. The received measurement data are recorded in a two-dimensional array. At least one echo trace is extracted from the array. A relative speed of the detected sound echoes with respect to the at least one sensor is determined using a derivative over time of the measurement data of the array. The at least one echo trace is classified based on the determined relative speed.

An apparatus for nautical tracking, where the apparatus detects at least one object. The apparatus further determines radar information associated with the at least one object, and calculates a first velocity vector associated with the at least one object. The apparatus further determines information associated with a tidal current of the water body, and calculates a second velocity vector based on the information associated with the tidal current. The apparatus further compares the first velocity vector and the second velocity vector in order to classify an object of the at least one object as a target, and further notifies a user of the target.

A computer-implemented method for monitoring a condition of a person includes receiving, at a computerized device, at least one signal from a condition sensor and determining if a condition is an emergency condition of a user based on the at least one signal.

An apparatus for nautical tracking, where the apparatus detects at least one object. The apparatus further determines radar information associated with the at least one object, and calculates a first velocity vector associated with the at least one object. The apparatus further determines information associated with a tidal current of the water body, and calculates a second velocity vector based on the information associated with the tidal current. The apparatus further compares the first velocity vector and the second velocity vector in order to classify an object of the at least one object as a target, and further notifies a user of the target.

A method for estimating a range of a moving target includes emitting, from a target, a first ultrasound signal T, wherein the first ultrasound signal T is generated based on a first differential Zadoff-Chu sequence x; receiving, at a receiver, a second ultrasound signal R, which corresponds to the first ultrasound signal T, wherein the second ultrasound signal R includes a second differential Zadoff-Chu sequence y; applying a maximum likelihood estimator to the first ultrasound signal T and the second ultrasound signal R to calculate an initial time of flight estimate tau.sub.corr; and calculating an initial range estimate d.sub.corr of the target by multiplying the initial time of flight estimate tau.sub.corr with a speed of sound c. A differential Zadoff-Chu sequence is different from a Zadoff-Chu sequence.

A method for estimating a range of a moving target includes emitting, from a target, a first ultrasound signal T, wherein the first ultrasound signal T is generated based on a first differential Zadoff-Chu sequence x; receiving, at a receiver, a second ultrasound signal R, which corresponds to the first ultrasound signal T, wherein the second ultrasound signal R includes a second differential Zadoff-Chu sequence y; applying a maximum likelihood estimator to the first ultrasound signal T and the second ultrasound signal R to calculate an initial time of flight estimate tau.sub.corr; and calculating an initial range estimate d.sub.corr of the target by multiplying the initial time of flight estimate tau.sub.corr with a speed of sound c. A differential Zadoff-Chu sequence is different from a Zadoff-Chu sequence.

A method comprising: providing an autonomous vehicle (AV) with a first estimated position of a target; directing the AV to travel toward the first estimated position at a constant velocity; receiving echo signals of transmitted sonar signals, the echo signals indicating a range and an azimuth of the target; determining a depth difference of the AV and the target based on the received echo signals, the depth difference being determined based on changes to the range and azimuth of the target over time; and in response to a depth difference existing, re-directing the AV toward a second estimated position of the target generated from the depth difference.

An electronic device includes a speaker configured to output an inaudible acoustic signal, one or more microphones configured to receive a first reflected wave signal, a memory storing one or more instructions, and one or more processors configured to execute the one or more instructions to obtain a signal change amount based on a correlation between a reference signal corresponding to the inaudible acoustic signal and the received first reflected wave signal, based on the signal change amount exceeding a first threshold value corresponding to a movement of an object, obtain object location information corresponding to a location of the object in a spatial structure based on the signal change amount, and based on the signal change amount exceeding a second threshold value corresponding to a change in the spatial structure, update a final parameter set corresponding to the inaudible acoustic signal by using a waveform optimization model.