When the radar system detects low-altitude, small, slow-moving (LSS) targets, the strong clutter interference from the ground will cause false alarms and affect the detection performance. In this paper, a phased array radar transmit beam steering algorithm is proposed to minimize strong interference from ground radiation. By minimizing the weighted vector norm and choosing variable sidelobe levels, the beam pattern can achieve deep notches in the ground-related area and maintain good main lobe detection performance. Furthermore, the designed beam should be insensitive to array mismatch and be robust. In addition, a peak-to-average power ratio (PAPR) constraint is introduced to fully utilize the transmitted energy. This optimization problem can be transformed into a second-order cone programming (SOCP) problem and solved using an off-the-shelf solver. The simulation results verify that the transmit beam synthesized by this method can meet the requirements of minimizing the main lobe loss and low side lobes on the ground side.

In radar detection, in order to make the beam have variable directivity, a Capon beamformer is usually used. Although this traditional beamformer enjoys both high resolution and good interference suppression, it usually leads to high sidelobe and is sensitive to array steering vector (ASV) mismatch. To overcome such problems, this study devises a novel, robust adaptive beamformer that is robust to ASV mismatch under the constraint where the sidelobe is oriented to the ground. Moreover, to make full use of the transmit power, the constraint of a low peak-to-average power ratio (PAPR) is also taken into consideration. Accordingly, this robust adaptive beamformer is developed by optimizing a transmitting beamformer constrained by ASV mismatch and low PAPR. This optimization problem is transformed into a second-order cone programming (SOCP) problem which can be efficiently and exactly solved. The proposed transmit beamformer possesses not only adaptive interference rejection ability and robustness against ASV mismatch, but also direct sidelobe control and a low PAPR. Simulation results are presented to demonstrate the superiority of the proposed approach. The proposed method can make the peak sidelobe level (PSL) level on the ground side below −30 dB.

Strong ground clutter echoes make it difficult to detect low-altitude slow-speed small (LSS) targets. To suppress ground clutter effectively in LSS target detection, a robust transmit beamforming algorithm has been proposed in this paper. Sidelobes in the ground side can be cut down, with the excess energy concentrated on the air side, which would be cleaner and simpler. The objective function is a second-order cone programming problem and can be solved by the convex optimization algorithm. With the consideration of taking full advantage of transmit power, the weight vector is further processed under the unimodular constraint. Numerical experiments are carried out to demonstrate the validity and superiority of the proposed method.

Transmit beamforming (TBF) provides the capability of focusing illuminating power in the desired directions while reducing the emitting power in undesired directions. It is significantly important in low-altitude and slow-speed small (LSS) radar, which usually suffers from heavy clutter and rapidly changing interference on the near-ground side. Due to nonideal factors such as an inaccurate target direction and array gain-phase error, the robustness of TBF is also necessary to consider in practical applications. In this paper, we provide a robust TBF method that enables sidelobe control in preset regions and possesses high transmit efficiency in virtue of the peak-to-average-power ratio (PAPR) constraint on transmit weights. To achieve robustness, a norm upper bound is introduced to limit the fluctuation of transmit weights, and the steering vector mismatch is also considered by using a spherical uncertainty set surrounding the nominal steering vector. As the proposed robust TBF is nonconvex because of the nonconvexity of both the objective function and constraints, we translate it into a series of convex subproblems via several kinds of convex relaxation schemes. In particular, based on the special structure of the objective function and constraints, the translation of the nonconvex problem into a tractable SOCP problem is realized by using the combination of the triangle inequality and Cauchy–Schwartz inequality. Numerical results demonstrate the improvement in the efficiency and robustness of the proposed TBF method in comparison with traditional TBF methods.

Low-altitude slow-moving small (LSS) targets are defined as flying at altitudes less than 1000 m with speeds less than 55 m/s and a radar crossing-section (RCS) less than 2 m2. The detection performance of ground-based radar using the LSS target detection technique can be significantly deteriorated by the diversity of LSS targets, background clutter, and the occurrence of false alarms caused by multipath interference. To address the LSS target detection problem, we have devised a novel two-dimensional electronic scanning active phased array radar system that is implemented in the software-defined radar architecture and propose a transmit beam control algorithm based on the low peak-to-average ratio (PAPR). Meanwhile, we devised a flexible arbitrary radar waveform generator to adapt to complex environmental situations. Field experiment results effectively demonstrate that our radar can be used to detect LSS targets. Moreover, an ablation experiment was conducted to verify the role played by transmit beam control and adaptive waveform optimization and generation in improving the system performance.