For successful beam shaping and scanning in phased array radars, it is essential to precisely set the amplitude and phase of each element channel. However, considerable amplitude and phase differences among the channels can occur due to the different RF hardware connected to each element. Also, the phase and amplitude characteristics of most RF devices depend on frequency and temperature and usually drift in time. In order to equalize the phase and amplitude effects of the channels, phased array radars need to be calibrated periodically. In the literature, various phased array calibration methods are discussed. However, the specifics of these methods are usually not covered. Here, we describe four of the most commonly used calibration methods in detail: near-field scanning probe, peripheral fixed probes, calibration lines, and mutual coupling. Each calibration method is described step by step and relevant formulas are given. The advantages and disadvantages of each method are also discussed.

3D imaging of Earth’s surface layers (such as canopy, sub-surface, or ice) requires not just the penetration of radar signal into the medium, but also the ability to discriminate multiple scatterers within a slant-range and azimuth resolution cell. The latter requires having multiple radar channels distributed in across-track direction. Here, we describe the theory of multi-static radar tomography with emphasis on resolution, SNR, sidelobes, and nearest ambiguity location vs. platform distribution, observation geometry, and different multi-static modes. Signal-based 1D and 2D simulations are developed and results for various observation geometries, target distributions, acquisition modes, and radar parameters are shown and compared with the theory. Pros and cons of multi-static modes are compared and discussed. Results for various platform formations are shown, revealing that unequal spacing is useful to suppress ambiguities at the cost of increased multiplicative noise. In particular, we demonstrate that the multiple-input multiple-output (MIMO) mode, in combination with nonlinear spacing, outperforms the other modes in terms of ambiguity, sidelobe levels, and noise suppression. These findings are key to guiding the design of tomographic SAR formations for accurate surface topography and vegetation mapping.

Recent results have highlighted the potential ability of bi- and multistatic synthetic aperture radar (SAR) tomographers to measure vegetation structure and surface topography. However, the quality of SAR tomographic measurements with multiple platforms is impacted by the phase instability in each platform’s oscillator. The phase noise, if uncompensated, may lead to degradation in the SAR data products such as increased sidelobe levels, reduced peak amplitude of the impulse response, and a low frequency phase modulation, among others. In this work, we model and examine the effects of oscillator phase noise on tomographic SAR signals for spaceborne missions flying in formation. A synchronization process is also adopted to help mitigate oscillator phase errors by measuring and predicting relative phase offsets at prescribed temporal intervals. A simulation tool was developed to examine the point target response as seen by realistic satellite constellations in low Earth orbit using different quality oscillators, radar configurations, and synchronization configurations. A first analysis of a multi-platform tomographic SAR mission suggests that a system without a dedicated physical link with minimal effects on the point target response may be achievable using current oscillators. Our analysis also shows that phase noise has differing effects on multistatic radar modes. Tomograms formed with a system operating in SIMO mode are the most affected by oscillator phase noise error, followed by MIMO, with negligible effects on the SAR-SISO mode. These trade studies and the simulation tool can be used to help inform the design of future multistatic radar missions.