Rapid developments in synthetic aperture (SA) systems, which generate a larger aperture with greater angular resolution than is inherently possible from the physical dimensions of a single sensor alone, are leading to novel research avenues in several signal processing applications. The SAs may either use a mechanical positioner to move an antenna through space or deploy a distributed network of sensors. With the advent of new hardware technologies, the SAs tend to be denser nowadays. The recent opening of higher frequency bands has led to wide SA bandwidths. In general, new techniques and setups are required to harness the potential of wide SAs in space and bandwidth. Herein, we provide a brief overview of emerging signal processing trends in such spatially and spectrally wideband SA systems. This guide is intended to aid newcomers in navigating the most critical issues in SA analysis and further supports the development of new theories in the field. In particular, we cover the theoretical framework and practical underpinnings of wideband SA radar, channel sounding, sonar, radiometry, and optical applications. Apart from the classical SA applications, we also discuss the quantum electric-field-sensing probes in SAs that are currently undergoing active research but remain at nascent stages of development.

An Overview of Advances in Signal Processing Techniques for Classical and Quantum Wideband Synthetic Apertures

Rapid developments in synthetic aperture (SA) systems, which generate a larger aperture with greater angular resolution than is inherently possible from the physical dimensions of a single sensor alone, are leading to novel research avenues in several signal processing applications. The SAs may either use a mechanical positioner to move an antenna through space or deploy a distributed network of sensors. With the advent of new hardware technologies, the SAs tend to be denser nowadays. The recent opening of higher frequency bands has led to wide SA bandwidths. In general, new techniques and setups are required to harness the potential of wide SAs in space and bandwidth. Herein, we provide a brief overview of emerging signal processing trends in such spatially and spectrally wideband SA systems. This guide is intended to aid newcomers in navigating the most critical issues in SA analysis and further supports the development of new theories in the field. In particular, we cover the theoretical framework and practical underpinnings of wideband SA radar, channel sounding, sonar, radiometry, and optical applications. Apart from the classical SA applications, we also discuss the quantum electric-field-sensing probes in SAs that are currently undergoing active research but remain at nascent stages of development. 

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In electronic warfare, the target is usually in a complex jamming environment. Cognitive waveform design is very important as an active and intelligent anti-jamming method. It is usually performed in the frequency domain and based on a single criterion, which is difficult to take into account the detection and anti-jamming performance and the operation is complex. Aiming at above problems, in the case of corner reflector jamming, a cognitive waveform design method based on multi-objective optimization criteria is proposed. We construct a multi-objective optimization model based on the maximum signal-to-jamming ratio (SJR), the minimum time delay resolution constant (TRC) and the minimum peak sidelobe ratio (PSLR). Then, it is converted into a single-objective function by the weighting method and solved by the particle swarm optimization (PSO) algorithm. The simulation results show that the method improves the signal-to-jamming ratio and range resolution of radar echoes and effectively enhances the ability of target detection and anti-jamming. 

Cognitive Radar Waveform Design Based on Multi-objective Optimization Criteria

The clutter background poses a challenge to the detection and recognition of targets from synthetic aperture radar (SAR) images, especially when the target is submerged by the clutter. In this paper, we propose a target-oriented SAR waveform optimization method to deal with this problem. The proposed method constructs an optimization criterion jointing the signal-to-clutter ratio (SCR) and the resolution of transmitted waveform. Based on the prior information of the frequency response of the interested target, the clutter suppression performance and the range resolution performance are jointly optimized. The simulation results show that the proposed method can effectively improve the SCR of SAR image in the condition of low SCR, while the resolution performance is guaranteed.

Target-Oriented Cognitive Sar Waveform Design Via Joint Optimization

In electronic warfare, the target is usually in a complex jamming environment. Cognitive waveform design is very important as an active and intelligent anti-jamming method. It is usually performed in the frequency domain and based on a single criterion, which is difficult to take into account the detection and anti-jamming performance and the operation is complex. Aiming at above problems, in the case of corner reflector jamming, a cognitive waveform design method based on multi-objective optimization criteria is proposed. We construct a multi-objective optimization model based on the maximum signal-to-jamming ratio (SJR), the minimum time delay resolution constant (TRC) and the minimum peak sidelobe ratio (PSLR). Then, it is converted into a single-objective function by the weighting method and solved by the particle swarm optimization (PSO) algorithm. The simulation results show that the method improves the signal-to-jamming ratio and range resolution of radar echoes and effectively enhances the ability of target detection and anti-jamming.

Intelligence technology has been widely used in various radar applications in recent years. However, there are few studies on the combination of intelligence technology and synthetic aperture radar (SAR). In this paper, a cognitive SAR waveform design method based on joint optimization criteria is proposed. The proposed method constructs a criteria jointing the resolution of SAR transmitting waveform and output SCNR. Cognitive SAR waveform designed upon this criterion solves the problem of weak clutter suppression and poor cognitive ability of conventional SAR. Meanwhile, it also solves the problem that the resolution performance of waveform designed based on the traditional criterion of maximum output SCNR is too poor to be used in SAR for high resolution missions. Simulation results show that the waveform designed by this method has high SCNR and great resolution.

Cognitive SAR Waveform Design Method Based on Joint Optimization Criteria

The invention provides a joint optimal criterion based waveform design method of a cognitive SAR. The method comprises the following steps that S1) a system parameter is initialized; S2) a joint optimal criterion objective function is established to maximize the echo SCNR and minimizing a time delay distinguishing constant; S3) a Lagrange multiplier method is used to convert the constraint optimization problem in the step S2) into a constraint-free optimization problem; S4) the constraint-free optimization problem in the step S3) is solved to obtain an expression of the optimal emission waveform based on the joint optimal criterion; and S5) according to an energy constraint condition, a Lagrange multiplier of the optimal emission waveform based on the joint optimal criterion in the step S4) is solved, and the optimal waveform is obtained. The emission waveform of the SAR is designed to use environment and target information, clutters are inhibited in the emission end, the SAR has a cognition capability, and the designed cognitive SAR has a higher distinguishing performance while inhibiting noises.

Joint optimal criterion based waveform design method of cognitive synthetic aperture radar (SAR)

Ground Moving Target Indication (GMTI) for Near-space Hypersonic vehicle borne Synthetic Aperture Radar (NH-SAR) is an important part of remote sensing applications. However, the ultra-long range and the ultra-high flight speed of NH-SAR causes the lower echo signal-to-noise ratio (SNR) and the expanded clutter spectrum, which reduces the performance of traditional GMTI methods such as Displaced Phase Centre Antennas (DPCA), along track interferometry (ATI) and Space Time Adaptive Processing (STAP). In this paper, a method based on Track Before Detect (TBD) in image domain is proposed to perform GMTI for NH-SAR. This method obtains the multi-frame images of NH-SAR firstly, and tracks the trajectories of the moving targets in the images. The simulation results validate the effectiveness of the proposed method, and show that this method has lower false alarm probabilities under the low-SNR condition.

Mafei Xu

Papers

Cognitive SAR Waveform Design Method Based on Joint Optimization Criteria

Joint optimal criterion based waveform design method of cognitive synthetic aperture radar (SAR)

A GMTI Method for Near-Space Hypersonic Vehicle-borne SAR based on Track Before Detect in Image Domain