Embodiments of the present disclosure describe an efficient O(n log n) method that implements the Inverse Chirp Z-Transform (ICZT). This transform is the inverse of the well-known forward Chirp Z-Transform (CZT), which generalizes the fast Fourier transform (FFT) by allowing the sampling points to fall on a logarithmic spiral contour instead of the unit circle. Thus, the ICZT can be viewed as a generalization of the inverse fast Fourier transform (IFFT).

An object detection device includes a signal generation unit, a drive unit, an object determination unit, and a drive control unit. The signal generation unit generates at least one pulse signal that includes an identification code for identifying the ultrasonic wave. The drive unit drives the wave transceiver unit using a current or a voltage according to the at least one pulse signal. The object determination unit compares a code included in the received ultrasonic wave with the identification code and determines whether the received ultrasonic wave is a wave resulting from reflection of the ultrasonic wave transmitted by the wave transceiver unit, and determines whether an object is present in a predetermined detection range based on the amplitude of the received ultrasonic wave. The drive control unit reduces the current or the voltage used by the drive unit when a predetermined amplitude rise time has elapsed.

A target positioning device and method based on a plecotus auritus double-pinna bionic sonar. An echo positioning device based on bionic pinnae of a bat can determine an azimuth and an elevation of a target to locate the spatial location of the target by using echoes obtained by two array elements, resolving a problem that two array element antennas cannot locate the space coordinates. In a positioning method based on bionic pinnae of a bat according to filtering characteristics of bat ears, a method for estimating a spatial location by a neural network is used, and a pulse string estimation method is used to reduce the error of estimated angles, to obtain a precise azimuth and elevation.

The disclosed systems, structures, and methods are directed to an object detection system, employing a receiver configured to receive a signal reflected from an object, an analog-to-digital converter (ADC) configured to convert the received signal into a digital signal, a pre-processor configured to improve a signal-to-noise (SNR) of the digital signal and to generate a pre-processed signal corresponding to the digital signal, a parameter extractor configured to calculate a number of reference cells M and a multiplication factor K.sub.0, and a Constant False Alarm Rate (CFAR) processor configured to analyze a cell-under-test (CUT) and M reference cells in accordance with the number of reference cells M and the multiplication factor K.sub.0 to detect the presence of the object.

A processor is configured to include a correlation object determination unit for establishing: a first to-be-correlated signal established on the basis of a first upper-limit rate of change, which is the rate of change of an upper-limit envelope of a direct wave signal, and a first lower-limit rate of change, which is the rate of change of a lower-limit envelope of the direct wave signal; and a second to-be-correlated signal established on the basis of a second upper-limit rate of change, which is the rate of change of an upper-limit envelope of a round-trip-delayed wave signal, and a second lower-limit rate of change, which is the rate of change of a lower-limit envelope of the round-trip-delayed wave signal. The processor is also configured to include a correlation processing unit for establishing a correlation value between the first to-be-correlated signal and a signal based on the second to-be-correlated signal.

The disclosed systems, structures, and methods are directed to an object detection system, employing a receiver configured to receive a signal reflected from an object, an analog-to-digital converter (ADC) configured to convert the received signal into a digital signal, a pre-processor configured to improve a signal-to-noise (SNR) of the digital signal and to generate a pre-processed signal corresponding to the digital signal, a parameter extractor configured to calculate a number of reference cells M and a multiplication factor K.sub.0, and a Constant False Alarm Rate (CFAR) processor configured to analyze a cell-under-test (CUT) and M reference cells in accordance with the number of reference cells M and the multiplication factor K.sub.0 to detect the presence of the object.

In the method for transmitting data representing an ultrasonic measurement signal of an ultrasonic measuring device, in particular for a vehicle, from a transmitter to a receiver a digitized analog ultrasonic measurement signal is provided in the transmitter. On the transmitter side the ultrasonic measurement signal is sampled at a multiple of its frequency and divided into individual successive blocks of sampling values. The sampling values of the sampled ultrasonic measurement signal are transformed in blocks into the frequency range. Those frequency portions of the spectrum whose amplitude is smaller than a presettable threshold value, or the frequency portions of the spectrum above an upper frequency limit value and/or below a lower frequency limit value are removed. The amplitude range covered by the remaining frequency spectrum is scaled by a scaling factor for further reduction of the data. The data of each block with the scaling factor assigned to the respective block are transmitted to the receiver. On the receiver side the scaling of the amplitude range of the frequency spectrum of each block is reversed using the respective scaling factor and the frequency spectrum is transformed back into the time range.

An object detection device includes: a transmission unit transmitting a first transmission wave; a reception unit receiving a first reception wave reflected by an object; a signal processing unit sampling a first processing target signal according to the first reception wave and acquiring a difference signal based on a difference between the first processing target signal for at least one sample at a certain detection timing, and the first processing target signal for a plurality of samples in at least one of first and second periods; a threshold setting unit setting a threshold as a comparison target with the value of the difference signal, based on variation in the values of the first processing target signal for the plurality of samples; and a detection unit detecting information about the object at the detection timing based on a comparison result between the value of the difference signal and the threshold.

Various sensors, sensor controllers, and sensor control methods are provided with model-based sideband balancing. In one illustrative embodiment, a controller for a piezoelectric transducer includes a transmitter, a receiver, and a processing circuit coupled to the transmitter and receiver. The processing circuit performs calibration and echo detection, the calibration including: sensing the piezoelectric transducer's phase response as a function of frequency; deriving equivalent circuit parameters for the piezoelectric transducer from the phase response; and determining a sideband imbalance based on one or more of the equivalent circuit parameters. Once the sideband imbalance is identified, the processing circuit may perform echo-detection processing that accounts for the sideband imbalance.

A method for detecting an object in a surrounding region of a motor vehicle is disclosed. In each of a plurality of temporally sequential measurement cycles a raw signal is received, which describes an ultrasonic signal of an ultrasonic sensor reflected in the surrounding region, the raw signal is compared with a predetermined ground threshold value curve, and a signal component of the raw signal that is to be tracked which exceeds the ground threshold value curve is detected and assigned to the object, and the object is tracked in the measurement cycles on the basis of the detected signal component that is to be tracked, wherein to track the object after recognition of the signal component that is to be tracked, in the subsequent measurement cycles, signal peaks of the raw signal are detected, and an assignment to the object is checked for the detected signal peaks.