Although the transmit radar waveform design problem for maximizing target information has been studied widely in the past, the resolution requirement is normally ignored in such designs. Using maximizing target information as a criterion, a new radar waveform design method meeting the high-resolution requirement is proposed in this article, which makes no assumptions on the statistical distribution of target scattering. The objective function is proposed by maximizing the Pearson correlation coefficient and the design is then transformed into an optimization problem, which is solved in two steps. First, a closed-form expression for the discretized waveform with constant power constraint is derived in the time domain. Second, based on the bandwidth analysis of the optimal solution, a resolution improvement method considering information distortion is introduced and a suboptimal waveform is proposed while satisfying the constant power and resolution requirements. Finally, performance of the proposed radar waveform in terms of information acquisition, classification, and resolution is analyzed and compared with the classic high-resolution linear frequency modulated waveform (LFMW). Simulation results show that the resolution of the suboptimal waveform is slightly lower than the LFMW, but more desirable in terms of peak sidelobe ratio, information acquisition, and classification.

In this paper, a joint design of both transmit waveform and imaging filters for synthetic aperture radar (SAR) is proposed to improve its information acquisition capability. First, the mutual information between SAR image and target scattering characteristics is considered as the performance metric, and its equivalent analytical version is derived in the 2-D frequency domain. The design is formulated as an optimization problem with an energy condition and a similarity constraint. Then, to tackle the resultant non-convex problem, by referring to the Dinkelbach's method, an algorithm is derived to find the desired solution via a cyclic maximization procedure alternating between three subproblems. Based on minorization-maximization, a unified optimization method with an increasing penalty on constraint violation is proposed to solve all subproblems. Convergence of the developed algorithm is analytically proved. Finally, numerical examples are presented to demonstrate the effectiveness of the proposed design.

A joint design of the transmit weight sequence and receive filter is proposed to improve target information acquisition in high-resolution radar. First, using the criterion for target information acquisition maximization, the design is cast as a nonconvex fractional quadratically constrained quadratic problem (QCQP). Then, by employing a bivariate auxiliary function introduced in Dinkelbach’s algorithm to decouple the fractional objective function, an algorithm with polynomial computational complexity is developed to solve the QCQP using a cyclic maximization procedure alternating between two semidefinite relaxation (SDR) problems. Through exploiting a suitable rank-one decomposition, it is verified that the optimal solution obtained from the alternative iterative process is also optimal to the original QCQP. Finally, numerical examples are presented to demonstrate the performance of the proposed design.

Radar is utilized as an active sensing device across many fields. Its waveform optimization is responsible for target signature extraction, profoundly influencing the overall performance. First, the principle of pulse radar waveform design is explored. Waveform design strategies vary based on target models, whether point-like or extended ones, and are often formulated as high-dimensional, non-convex optimization problems with multiple constraints, such as energy, constant modulus, and sidelobe ratios. Second, to address them, techniques like alternating direction method of multipliers (ADMM), semidefinite relaxation (SDR), and minimization-maximization (MM) algorithms are widely employed. Finally, challenges in multimodal sensing collaborative detection, joint multi-tasking, sparse signal recovery, and intelligent perception highlight the need for innovative solutions to meet future demands.

The carrier frequency and bandwidth are vital parameters of radar transmit signals. In this paper, a joint design of frequency and bandwidth in multi-frequency synthetic aperture radar (SAR) is proposed to improve the target information acquisition capability. First, the target detection mutual information is considered as the performance metric, and its mathematical expression is derived using the example of decision-level fusion and hypothesis testing. The design is formulated as an optimization problem with multiple engineering constraints based on mutual information maximization. Then, a modified genetic algorithm is proposed to find the optimal solution satisfying the constraints via a code adjustment operator. It is shown by simulation results that, for a specific scene, the multi-frequency SAR with its frequencies and bandwidths designed by the proposed method has higher target information acquisition capability and more accurate target detection performance than existing spaceborne SAR systems.

To enhance the signature of an extended target in a SAR image, a robust waveform design method is presented for spectrally dense environments. First, the problem is formulated by maximizing the worst-case signal-to-clutter ratio (SCR) over the uncertainty set of statistics for both target and background scattering characteristics, subject to energy, similarity, and spectrum constraints. Second, the closed-form solutions for the uncertain statistics are derived. The problem of maximizing worst-case SCR is boiled down to a nonconvex fractional quadratically constrained quadratic problem (QCQP). Resorting to the Dinkelbach’s algorithm and Lagrange duality, the QCQP is split into a series of solvable semidefinite programming problems. A convergence analysis is conducted, where a sufficient condition for global convergence is derived. Finally, numerical examples are presented to demonstrate the performance of the proposed scheme.