Chaos Based Frequency Modulation for Joint Monostatic and Bistatic Radar-Communication Systems

In this article, we propose the utilization of chaos-based frequency modulated (CBFM) waveforms for joint monostatic and bistatic radar-communication systems. Short-duration pulses generated via chaotic oscillators are used for wideband radar imaging, while information is embedded in the pulses using chaos shift keying (CSK). A self-synchronization technique for chaotic systems decodes the information at the communication receiver and reconstructs the transmitted waveform at the bistatic radar receiver. Using a nonlinear detection scheme, we show that the CBFM waveforms closely follow the theoretical bit-error rate (BER) associated with bipolar phase-shift keying (BPSK). We utilize the same nonlinear detection scheme to optimize the target detection at the bistatic radar receiver. The ambiguity function for both the monostatic and bistatic cases resembles a thumbtack ambiguity function with a pseudo-random sidelobe distribution. Furthermore, we characterize the high-resolution imaging capability of the CBFM waveforms in the presence of noise and considering a complex target.

Anti-jamming approach based on radar transmitted waveform matching

This study proposes a novel approach to suppress noise jamming and smart jamming. The traditional method of using auxiliary channels to cancel interference requires pure interference samples to calculate weights, which is almost impossible for pulsed interference signals. In this work, to avoid the difficulty of choosing suitable interference samples, we construct the parameterized expected signal according to the time-delay relation between target reflecting echo and transmitted signal. The objective function is established in the form of the minimum mean square error between the recovered signal and the expected signal. The optimization problem is solved by an alternating iteration method. Simulation results demonstrate that the proposed method achieves excellent performance for suppressing noise jamming and smart jamming and is not sensitive to signal-to-noise ratio and jamming-to-noise ratio. The processing results of the measured data show that the method has a certain practical application value.

A Waveform-Encoded SAR Implementation Using a Limited Number of Cyclically Shifted Chirps

Synthetic aperture radar (SAR) provides high-resolution images of the Earth’s surface irrespective of sunlight and weather conditions. In conventional spaceborne SAR, nadir echoes caused by the pulsed operation of SAR may significantly affect the SAR image quality. Therefore, the pulse repetition frequency (PRF) is constrained within the SAR system design to avoid the appearance of nadir echoes in the SAR image. As an alternative, the waveform-encoded SAR concept using a pulse-to-pulse variation of the transmitted waveform and dual-focus postprocessing can be exploited for nadir echo removal and to alleviate the PRF constraints. In particular, cyclically shifted chirps have been proposed as a possible waveform variation scheme. However, a large number of distinct waveforms is required to enable the simple implementation of the concept. This work proposes a technique based on the Eulerian circuit for generating a waveform sequence starting from a reduced number of distinct cyclically shifted chirps that can be effectively exploited for waveform-encoded SAR. The nadir echo suppression performance of the proposed scheme is analyzed through simulations using real TerraSAR-X data and a realistic nadir echo model that shows how the number of distinct waveforms and therefore the system complexity can be reduced without significant performance loss. These developments reduce the calibration burden and make the concept viable for implementation in future SAR systems.

Adaptive Radar Waveform Design Based on Weighted MI and the Difference of Two Mutual Information Metrics

This study deals with the problem of radar waveform design based on the weighted mutual information (MI) and the difference of two mutual information metrics (DMI) in signal-dependent interference. Since the target and clutter information are included in the received signal at the beginning of the design, DMI-based waveform is designed according to the following criterion: maximizing the MI between the received signal and target impulse response while minimizing the MI between the received signal and the clutter impulse response. This criterion is equivalent to maximizing the difference between the first MI and the second MI. Then maximizing the difference of two types of MI is used as the objective function, and the optimization model with the transmitted waveform energy constraint is established. In order to solve it, we resort to maximum marginal allocation (MMA) method to find the DMI-based waveform. Since DMI-based waveform does not allocate energy to the frequency band where the clutter power spectral density (PSD) is greater than the target PSD, we propose to weight the MI-based waveform and DMI-based waveform to synthesize the final optimal waveform. It could provide different trade-offs between two types of MI. Simulation results show the proposed algorithm is valid.

Robust Waveform Design Based on Bisection and Maximum Marginal Allocation Methods with the Concept of Information Entropy

Cognitive radar can overcome the shortcomings of traditional radars that are difficult to adapt to complex environments and adaptively adjust the transmitted waveform through closed-loop feedback. The optimization design of the transmitted waveform is a very important issue in the research of cognitive radar. Most of the previous studies on waveform design assume that the prior information of the target spectrum is completely known, but actually the target in the real scene is uncertain. In order to simulate this situation, this paper uses a robust waveform design scheme based on signal-to-interference-plus-noise ratio (SINR) and mutual information (MI). After setting up the signal model, the SINR and MI between target and echo are derived based on the information theory, and robust models for MI and SINR are established. Next, the MI and SINR are maximized by using the maximum marginal allocation (MMA) algorithm and the water-filling method which is improved by bisection algorithm. Simulation results show that, under the most unfavorable conditions, the robust transmitted waveform has better performance than other waveforms in the improvement degree of SINR and MI. By comparing the robust transmitted waveform based on SINR criterion and MI criterion, the influence on the variation trend of SINR and MI is explored, and the range of critical value of Ty is found. The longer the echo observation time is, the better the performance of the SINR-based transmitted waveform over the MI-based transmitted waveform is. For the mutual information between the target and the echo, the performance of the MMA algorithm is better than the improved water-filling algorithm.

PRELIMINARY QUALITY ANALYSIS OF GF-7 SATELLITE LASER ALTIMETER FULL WAVEFORM DATA

The full-waveform data is the core data of GaoFen-7 (GF-7) satellite laser altimeter, and evaluation of waveform data quality is an important step and premise for satellite laser altimetry and quality control. In this paper, the full waveform data quality assessment and analysis of GF-7 laser altimeter is implemented during the period of on-orbit experiment, and the real waveform data of many orbits is used to quantitatively describe the characteristic parameters of the transmitted waveform and the signal-to-noise ratio (SNR), and the result of two beam lasers is compared. The conclusion is validated that the GF-7 laser altimeter can obtain effective waveform data and the echo waveform availability of the experimental data is approximate 72.59%, moreover, the quality of beam 1 is slightly better than that of the beam 2. The laser temperature is an important indication of the quality of transmitted waveform according to the SNR changing. The good SNR value of the waveform and small footprint size will be helpful for the terrain information extraction and analysis, although the repetition frequency is low.

Multi-Target Robust Waveform Design Based on Harmonic Variance and Mutual Information

Cognitive radar is an intelligent radar system, and adaptive waveform design is one of the core problems in cognitive radar research. In the previous studies, it is assumed that the prior information of the target is known, and the definition of target spectrum variance has not changed. In this paper, we study on robust waveform design problem in multiple targets scene. We hope that the upper and lower bounds of the uncertainty range of robustness are more close to the actual situation, and establish a finite time random target signal model based on mutual information (MI). On the basis of the optimal transmitted waveform and robust waveform based on MI, we redefine the target spectrum variance as harmonic variance, and propose a novel robust waveform design method based on harmonic variance and MI. We compare its performance with robust waveform based on original variance. Simulation results show that, in the situation of multiple targets, compared to the original variance, the MI lifting rate of robust waveform based on harmonic variance relative to the optimal transmitted waveform in the uncertainty range has great improvement. In certain circumstances, robust waveform based on harmonic variance and MI is more suitable for more targets.

Talbot Algorithm with a Trapezoidal Wave in the 2.5D Airborne Transient Electromagnetic Method in Marine Investigations

The airborne transient electromagnetic (TEM) method is widely used in land applications but faces challenges in marine applications due to the strong masking effects of seawater. The accuracy of the inverse Laplace transform algorithm strongly affects the applicability of the 2.5D TEM method in marine research; thus, an appropriate transmitted waveform is required. To resolve these issues, a trapezoidal wave was utilized as the waveform of the current source, owing to the substantial energy contribution of the low-frequency range. Further, the Talbot algorithm was selected for the inverse Laplace transform as it can yield an accurate response with smaller summation terms than the commonly used Gaver–Stehfest (G-S) algorithm. On this basis, a rugged seabed and a subsea tunnel were also investigated. The voltage response is obtained when the flight heights of the loop source change. The results confirmed that the Talbot algorithm with a trapezoidal waveform is more reliable and robust for complex marine geological models and is expected to provide an effective approach for marine explorations.