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HF radar systems are widely used for the measurement of ocean surface currents and wave parameters. Theoretical analysis of high frequency radio wave backscattering from the sea has been derived in the past. Also, the relationship between Bragg frequencies and surface currents is determined and has been proved by HF radars. It is known that when surface currents are present, the Bragg frequencies move to new frequencies. Their movement is proportional to the surface current in the direction toward radar. In addition, it is observed that sea surface current changes the second order part of the spectrum of radar reflection from the sea surface. In this paper, a theoretical analysis of high-frequency radio wave backscattering from the sea in the presence of constant surface current provides a formula for the second order part of the spectrum of sea echo. This resulted in similar formulas of others but the process of formula extraction is different. This method may be used for the determination of the second order spectra of radar cross section in the presence of other types of surface current.

We propose a novel robust design method to jointly optimize the radar transmit code and receive filter, exploiting the signal-to-interference-plus-noise ratio (SINR) at the receiver end as design figure of merit. We confer robustness to our method against uncertainties on the target impulse response (TIR) using a worst-case optimization approach. Precisely, we model the uncertainty set as a finite collection of TIRs, obtained sampling the actual TIR at some aspect angles. We further enforce a peak-to-average power ratio (PAR) constraint to the transmit code, which is very important for radar applications, where the transmitter operates close to saturation. The design problem is tackled using a sequential optimization procedure alternating between two semi-definite programming (SDP) problems, followed by randomization steps. Our numerical results highlight the robustness and applicability of the proposed method.

We propose a novel robust design method to jointly optimize the radar transmit code and receive filter, exploiting the Signal-to-Interference plus Noise Ratio (SINR) at the receiver end as design figure of merit. We confer robustness to our method against uncertainties on the target impulse response (TIR) using a worst-case optimization approach based on two different uncertainty sets. The former is composed of a finite collection of TIRs, obtained by sampling the actual TIR at some aspect angles; the latter is a spherical uncertainty set. We further enforce a peak-to-average power ratio (PAR) constraint to the transmit code, which is very important for radar applications where the transmitter operates close to saturation. The design problem is tackled using a sequential optimization procedure alternating between two semi-definite programming (SDP) problems, followed by randomization steps. Our numerical results highlight the robustness and applicability of the proposed method in different scenarios.

A multiple-input multiple-output (MIMO) radar system., unlike a standard phased array radar., can choose freely the probing signals transmitted via its antennas to maximize the power around the locations of the targets of interest., or more generally to approximate a given transmit beam-pattern., or to minimize the cross-correlation of the signals reflected back to the radar by the targets of interest. In this paper it will be shown that how these more degrees of freedom to choose freely between probing signals in a MIMO radar can help to have an omnidirectional beam-pattern for a side-lobe blanker system., and it will be shown that with utilizing MIMO radars for a side-lobe blanker system., one can achieve immunity respect to faults that may occurred during build processes.

A multiple input multiple output (MIMO) radar system is an emerging research field which has attracted many studies in recent years. This type of radar, unlike conventional phased array radar, can transmit different probing signals via its antennas, that may be correlated or uncorrelated with each other. This waveform diversity offered by MIMO radar systems enable superior capabilities compared to conventional phased array radar. Many papers have introduced different ways for beamforming of MIMO radar. In this paper it is desirable to analysis some methods for beamforming of MIMO radars with planar arrays constellation and examine their 3D result beam-pattern of such constellations for covariance based MIMO radar waveforming method. MATLAB software is being employed for simulations.

The problem of detection of coherent radar signals with unknown Doppler shift in noise plus clutter, which is assumed to be gaussian is addressed. The authors solve the detection problem and find the optimum ALR detector. Since it includes a difficult integral, they derive several suboptimum detectors including CGLR, AALR and CALR. Comparison of these detectors via computer simulations shows that CALR and CGLR can have near-optimum performance whereas the common radar-detectors may have severe losses.