Radar system with coordinate calibration for improved angular resolution
US-2024053437-A1 · Feb 15, 2024 · US
US2024361426A1 · US · A1
| Field | Value |
|---|---|
| Publication number | US-2024361426-A1 |
| Application number | US-202318309513-A |
| Country | US |
| Kind code | A1 |
| Filing date | Apr 28, 2023 |
| Priority date | Apr 28, 2023 |
| Publication date | Oct 31, 2024 |
| Grant date | — |
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Systems, methods, and apparatus for denoising signals are disclosed. In one aspect, an apparatus is provided. The apparatus may comprise a first denoiser configured to receive an input signal and to generate a denoised signal and a signal reverser configured to receive the input signal and to generate a time reversed signal. The apparatus may also include a second denoiser configured to receive the time reversed signal and to generate a denoised time reversed signal. Further, the apparatus may include a signal combiner configured to combine the denoised signal with the denoised time reversed signal to generate an output signal.
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What is claimed is: 1 . An apparatus comprising: a first denoiser configured to receive an input signal and to generate a denoised signal; a signal reverser configured to receive the input signal and to generate a time reversed signal; a second denoiser configured to receive the time reversed signal and to generate a denoised time reversed signal; and a signal combiner configured to combine the denoised signal with the denoised time reversed signal to generate an output signal. 2 . The apparatus according to claim 1 , further comprising a receiver configured to receive a mixture of signals, wherein the receiver is configured to digitize the mixture of signals to generate the input signal, and wherein the mixture of signals comprises a noise signal and one or more waveform signals from one or more sources. 3 . The apparatus according to claim 1 , wherein the input signal is a time-series of data points of a mixture of signals, wherein the denoised signal is an estimate of a signal of interest, and wherein the denoised time reversed signal is an estimate of a time reversal of the signal of interest. 4 . The apparatus according to claim 2 , further comprising an antenna configured to receive radio frequency (RF) signals or radar signals and to generate the mixture of signals. 5 . The apparatus according to claim 2 , wherein the receiver includes an analog-to-digital converter (ADC), and wherein the ADC is configured to digitize the mixture of signals to generate the input signal. 6 . The apparatus according to claim 5 , wherein the receiver further comprises an amplifier that amplifies the mixture of signals before the mixture of signals is received by the ADC, and wherein the amplifier amplifies the mixture of signals to a predetermined amplitude for sampling by the ADC. 7 . The apparatus according to claim 1 , wherein the signal combiner is configured to add the denoised signal and the denoised time reversed signal to generate the output signal, wherein the denoised signal includes near-zero phase error and near-zero phase delay, and wherein the denoised time reversed signal includes near-zero phase error and near-zero phase delay. 8 . The apparatus according to claim 1 , wherein the first denoiser includes a first multi-pole filter, wherein the first multi-pole filter is configured to filter and/or shape the input signal, and wherein the second denoiser includes a second multi-pole filter, wherein the second multi-pole filter is configured to filter and/or shape the denoised reversed time signal. 9 . The apparatus according to claim 1 , wherein the first denoiser is configured to process the input signal using a first neural network to generate the denoised signal, and wherein the second denoiser is configured to process the time reversed signal using a second neural network to generate the denoised time reversed signal. 10 . The apparatus according to claim 1 , wherein the first denoiser comprises a plurality of neural network reservoirs that interact with each other to enhance detection of the input signal, and wherein the second denoiser comprises a plurality of neural network reservoirs that interact with each other to enhance detection of the input signal. 11 . The apparatus according to claim 1 , wherein the first denoiser is configured to: linearly mapping the input signal to reservoir states of a dynamical reservoir; generating a high-dimensional state-space representation of the input signal by combining the input signal with the reservoir states; denoising the reservoir states by removing noise from each reservoir state signal; and generating the denoised signal by combining the denoised reservoir states. 12 . The apparatus according to claim 11 , wherein the second denoiser is configured to: linearly mapping the time reversed signal to reservoir states of a dynamical reservoir; generating a high-dimensional state-space representation of the time reversed signal by combining the time reversed signal with the reservoir states; denoising the reservoir states by removing noise from each reservoir state signal; and generating the denoised time reversed signal by combining the denoised reservoir states. 13 . The apparatus according to claim 1 , further comprising a transmitter for transmitting a radio frequency (RF) signal or a radar signal. 14 . A method comprising: denoising, at one or more denoisers, an input signal to generate a denoised signal; performing a time-reversal operation on the input signal to generate a time reversed signal of the input signal; denoising, at the one or more denoisers, the time reversed signal to generate a denoised time reversed signal; and generating an output signal based on the denoised signal and the denoised time revered signal. 15 . The method according to claim 14 , wherein the input signal is a time-series of data points of a mixture of signals, wherein the denoised signal is an estimate of a signal of interest, and wherein the denoised time reversed signal is an estimate of a time reversal of the signal of interest. 16 . The method according to claim 14 , further comprising generating the input signal based on a mixture of signals, and wherein the mixture of signals comprises a noise signal and one or more waveform signals from one or more sources. 17 . The method according to claim 14 , wherein the output signal is generated by adding the denoised signal and denoised time reversal signal, wherein the denoised signal includes near-zero phase error and near-zero phase delay, and wherein the denoised time reversed signal includes near-zero phase error and near-zero phase delay. 18 . The method according to claim 14 , wherein the one or more denoisers includes a first denoiser and a second denoiser, wherein the first denoiser includes a first multi-pole filter, wherein the first multi-pole filter is configured to filter and/or shape the input signal, and wherein the second denoiser includes a second multi-pole filter, wherein the second multi-pole filter is configured to filter and/or shape the denoised reversed time signal. 19 . The method according to claim 14 , wherein denoising the input signal further comprises processing the input signal using a first neural network, and wherein denoising the time reversed signal further includes processing the time reversed signal using a second neural network. 20 . A non-transitory computer-readable medium having stored thereon instruction code, wherein the instruction code is executable by one or more processors to perform operations comprising: denoising an input signal to generate a denoised signal; generating a time reversed signal of the input signal; denoising the time reversed signal to generate a denoised time reversed signal; and generating an output signal by combining the denoised signal with the denoised time revered signal.
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