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Santiago Ozafrain

Publications and source records attributed to Santiago Ozafrain.

2 recordsLinked to original sources

Characterizing the Effects of Mixed Division Waveform Schemes in MIMO Radar

Direction of departure estimation in Multiple-Input-Multiple-Output (MIMO) radar is based on transmitting a set of orthogonal (or at least separable) waveforms, one per transmit element. Assuming orthogonality is preserved, these waveforms can then be separated into different channels at the receiver before beamforming. In practice, however, MIMO waveforms are not perfectly orthogonal, and at different points in the processing chain, this can manifest as phase errors in the steering manifolds used in beamforming. Furthermore, due to resource constraints, either by the channel or the sensing scenario, a mixture of orthogonality techniques, mixed division strategies, are often employed, resulting in further phase errors. Naturally, such errors will interfere in the beamforming process, spoiling the beam, introducing direction finding errors, or increasing sidelobe levels, and consequently reducing SNR. In this paper, we demonstrate how mixing division strategies significantly degrades orthogonality of otherwise orthogonal waveforms resulting in degraded beamforming performance. Specifically, we show that waveforms which exhibit favourable sidelobe levels may still induce large direction of departure errors and vice versa. Additionally, through multiple exhaustive searches of potential mixed division strategies with combinations of time-, Doppler- and code-based division techniques we show that large numbers of the possible waveforms exhibit poor beamforming qualities.

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MIMO Array Calibration in Non-stationary Channels with Residual Surfaces and Slepian Spherical Harmonics

The fundamental mechanism driving MIMO beamforming is the relative phases of signals departing the transmit array and arriving at the receive array. If a propagation channel affects all transmitted signals equally, the relative phases are a function of the directions of departure and arrival, as well as the transmit and receive hardware. In a non-stationary channel, the amplitudes and phases of arriving signals may vary significantly over time, making it infeasible to directly measure the influence of hardware. In this paper, we present a calibration method for achieving indirect measurement and compensation of hardware influences in non-stationary channels. Our method characterizes the patterns of array elements relative to a reference element and estimates these relative patterns, termed residual surfaces, using a Slepian spherical harmonic basis. Using simulations, we demonstrate that our calibration method achieves beamforming gains that closely match theoretical optimums. Our results also show a reduction in the error in estimating the target direction, lower side lobes, and improve null-steering capabilities.

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