• Patent Title: Method for separating targets and clutter from noise, in radar signals
  • Application No.: US16479732
    Application Date: 2018-01-24
  • Publication No.: US11650286B2
    Publication Date: 2023-05-16
  • Inventor: Ronit Roxana Fuchs
  • Applicant: ARBE ROBOTICS LTD.
  • Applicant Address: IL Tel Aviv
  • Assignee: ARBE ROBOTICS LTD.
  • Current Assignee: ARBE ROBOTICS LTD.
  • Current Assignee Address: IL Tel Aviv
  • Agency: Zaretsky Group PC
  • Agent Howard Zaretsky
  • Priority: IL 0253 2017.01.24
  • International Application: PCT/IL2018/050091 2018.01.24
  • International Announcement: WO2018/138725A 2018.08.02
  • Date entered country: 2019-07-22
  • Main IPC: G01S7/35
  • IPC: G01S7/35 G01S13/34 G01S13/93
Method for separating targets and clutter from noise, in radar signals
Abstract:
A method for separating large and small targets from noise in radar IF signals, according to which a receiver receives, echo signals that are reflected from targets of different size (such as walls or ground), in response to the transmission of chirp FMCW radar signals, modulated (e.g., using Linear Frequency Modulation) in a predetermined modulation speed for a predetermined duration. The echo signals are down-converted by mixing them with the transmitted signal, to obtain received Intermediate Frequency (IF) signal, which is then sampled both in phase (I-channel) and in quadrature phase (Q-channel). The received IF signal passes a Fourier transform, to obtain power spectral components that belong to a relevant frequency domain, associated with an echo signal reflected from a real target, along with corresponding power spectral components that belong to an irrelevant, opposite frequency domain. The noise distribution and level in the relevant frequency domain is calculated by estimating the noise level in the irrelevant frequency domain and targets represented by a set of consequent relevant frequencies are detected by comparing the power spectral component at each relevant frequency to the calculated noise level and identifying power spectral components with likelihood, which is above a predetermined threshold.
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