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Moeness G Amin - One of the best experts on this subject based on the ideXlab platform.

  • maximum signal to noise ratio gps anti jam Receiver with subspace tracking
    International Conference on Acoustics Speech and Signal Processing, 2005
    Co-Authors: Moeness G Amin
    Abstract:

    We propose an anti-jam GPS Receiver which suppresses interference by projecting the received signal on the noise subspace obtained via subspace tracking. The resulting interference-free signal is then processed by a beamformer, whose weight vector is obtained by maximizing the signal-to-noise ratio at the beamformer Output. It is shown that the proposed Receiver can effectively eliminate interference and enhance the GPS signals at the Receiver Output.

  • ICASSP (4) - Maximum signal-to-noise ratio GPS anti-jam Receiver with subspace tracking
    Proceedings. (ICASSP '05). IEEE International Conference on Acoustics Speech and Signal Processing 2005., 1
    Co-Authors: W. Sun, Moeness G Amin
    Abstract:

    We propose an anti-jam GPS Receiver which suppresses interference by projecting the received signal on the noise subspace obtained via subspace tracking. The resulting interference-free signal is then processed by a beamformer, whose weight vector is obtained by maximizing the signal-to-noise ratio at the beamformer Output. It is shown that the proposed Receiver can effectively eliminate interference and enhance the GPS signals at the Receiver Output.

Shinsaku Mori - One of the best experts on this subject based on the ideXlab platform.

  • ICASSP (2) - Weak radar signal detection based on wavelet transform
    Proceedings of ICASSP '94. IEEE International Conference on Acoustics Speech and Signal Processing, 1
    Co-Authors: Naoki Ehara, Iwao Sasase, Shinsaku Mori
    Abstract:

    Weak signal detection is a basic and important problem in radar systems. The detectable range of a radar is determined by the radar equation. This equation shows that the performance of a radar is improved by increasing the Receiver Output SNR. For the purpose of improving the SNR, the process called "integration of pulses" has been used. We propose new methods based on the wavelet transform for the improvement of the SNR. The wavelet transform is a tool for time-frequency domain signal analysis and is sensitive to the transient signals. By computer simulations, we show that the Receiver Output SNR after the wavelet transform is applied becomes about 8 dB greater than that of the original signals. This value corresponds to a 60 percent improvement of the radar detectable range. >

Junji Ohtsubo - One of the best experts on this subject based on the ideXlab platform.

Predrag Spasojevic - One of the best experts on this subject based on the ideXlab platform.

  • Spectral and Spatial Properties of Antennas for Transmitting and Receiving UWB Signals
    IEEE Transactions on Vehicular Technology, 2008
    Co-Authors: Guofeng Lu, Larry J. Greenstein, Predrag Spasojevic
    Abstract:

    The spectral and spatial properties of antennas for transmitting and receiving ultrawideband (UWB) pulses and the corresponding filter response designs for receiving such pulses over severe multipath are studied in this paper. Based on the transmit and receive transfer functions of a UWB antenna, we analyze the UWB link behavior. A metric that is based on the Receiver Output signal-to-noise ratio (SNR) in multipath is used as a criterion to design an appropriate receive filter response. A lower bound on this metric allows for a tractable maximization. The solution is a linear combination of incoming pulses from all directions, which are weighted by their relative intensity. A simpler best candidate solution for the receive filter response is shown to provide a performance close to that of the linear combination solution. These results are given for a diamond planar antenna and a Gaussian monopulse at the transmitter side. For this case, the impact of direction angle on the Receiver Output SNR is also shown.

Kenji Kusumoto - One of the best experts on this subject based on the ideXlab platform.