Embodiments pertain to signal identification in a wideband spectrum. Some embodiments pertain to determining angle-of-arrival (AOA), frequency and bandwidth characteristics of the identified signals.
One issue with conventional wideband spectral estimation techniques is that they necessarily have to channelize input data prior to performing spatial-spectral estimation. This is because the array manifold vectors are defined at a specific signal frequency which creates errors when the signal frequency is not equal to the frequency used in the array manifold vector for the spatial-spectral estimation technique. Furthermore, wideband signals that extend through channels have challenges as they are processed in separate channels and have to be stitched back together or reconciled prior to reporting angle of arrival.
Thus, there are general needs for improved wideband spectral estimation.
The following description and the drawings sufficiently illustrate specific embodiments to enable those skilled in the art to practice them. Other embodiments may incorporate structural, logical, electrical, process, and other changes. Portions and features of some embodiments may be included in, or substituted for, those of other embodiments. Embodiments set forth in the claims encompass all available equivalents of those claims.
Embodiments disclosed herein utilize the joint space-time relationship of electromagnetic waves to define array manifold vectors in 4-dimensional space and overcome the lack of sample diversity in the z-dimension for planar arrays by introducing a known random time delay in each channel of the receiving array. Some embodiments perform 4-dimensional processing of incoming electromagnetic waves. Some embodiments perform Latin hypercube sampling of the k-space to determine array manifold vectors. Some embodiments perform randomized channel-to-channel delays prior to the formation of the covariance matrix utilized in spectral-estimation techniques. These embodiments are discussed in more detail below.
In some embodiments, the processing circuitry 106 may form the array manifold vectors in k-space (i.e., wave number space), each manifold vector having a length (m) corresponding with a number of channels.
In some embodiments, each receive channel may comprise a same wideband frequency spectrum. Each receive channel may be associated with one antenna element 102 of the array of antenna elements. For each receive channel, one of the random time delays may be applied to the received signals of the associated receive channel.
In some embodiments, the processing circuitry 106 may compute the inverse (Q) of the joint-space time spectral estimate (P) by projecting the array manifold vectors through the mixing matrix (M) yields. In some embodiments, the processing circuitry 106 may invert the inverse (Q) of the joint-space time spectral estimate (P) to obtain the joint-space time spectral estimate (P) 109.
In some embodiments, the processing circuitry 106 may form a sample covariance matrix (Sxx) from the time-delayed samples (Xn) and invert the sample covariance matrix to form the mixing matrix (M). In these embodiments, the sample covariance matrix (Sxx) may be an N×N Hermitian matrix.
In some embodiments, the processing circuitry 106 may identify signals (see
In some embodiments, the system may further comprise delay circuitry 104. The delay circuitry 104 may comprise a discrete time delay unit (TDU) 114 for each receive channel. Each of the TDUs may be configured to delay signals within one of the receive channels by the random time delay (tn) for that receive channel. In some embodiments, the discrete delay times are randomly set using control words to yield different delay times, although the scope of the embodiments is not limited in this respect.
In some embodiments, each array manifold vector (Vn) is computed using the following equation:
vn=ej(k
where pn represents position vectors corresponding to a position of an element, k represents the k-space vectors, K is the wavenumber, and tn represents the random time delay applied to a receive channel.
In some embodiments, the memory 110 may store the random time delay (τn) for each receive channel.
In these embodiments, the inverse (Q) of the joint-space time spectral estimate (P) may be computed in operation 212 by projecting the array manifold vectors through the mixing matrix (M) yields and operation 214 may comprise inverting the inverse (Q) of the joint-space time spectral estimate (P) to obtain the joint-space time spectral estimate (P).
In some embodiments, operation 208 may comprise forming a sample covariance matrix (Sxx) from the time-delayed samples (Xn) and operation 210 may comprise inverting the sample covariance matrix to form the mixing matrix (M).
In some embodiments, operations 208, 210, 212 and 214 may form the high-resolution spectrum as described by J. Capon, “High-resolution frequency-wavenumber spectrum analysis,” Proc IEEE, vol 57, pp 1408-1418, August 1969, although the scope of the embodiments is not limited in this respect.
e(r,t)≅E·ej(k
At an array whose location is at r at time t the signal at channel n can be expressed as:
en(r,t)≅E·ej(k
In these embodiments, the array manifold vector can be re-written as:
vn(r,t)=ej(k
In these embodiments, the time delay, tn, (see
Accordingly, a joint-space time spectral estimate (P) 109 may be determined by projecting the array manifold vectors through a mixing matrix (M) which is based on time-delayed samples (Xn) of the received signals.
Embodiments may be implemented in one or a combination of hardware, firmware and software. Embodiments may also be implemented as instructions stored on a computer-readable storage device, which may be read and executed by at least one processor to perform the operations described herein. A computer-readable storage device may include any non-transitory mechanism for storing information in a form readable by a machine (e.g., a computer). For example, a computer-readable storage device may include read-only memory (ROM), random-access memory (RAM), magnetic disk storage media, optical storage media, flash-memory devices, and other storage devices and media. Some embodiments may include one or more processors and may be configured with instructions stored on a computer-readable storage device.
The Abstract is provided to comply with 37 C.F.R. Section 1.72(b) requiring an abstract that will allow the reader to ascertain the nature and gist of the technical disclosure. It is submitted with the understanding that it will not be used to limit or interpret the scope or meaning of the claims. The following claims are hereby incorporated into the detailed description, with each claim standing on its own as a separate embodiment.
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20220120673 A1 | Apr 2022 | US |