Frame synchronization detection before data transmission is an important module which directly affects the lifetime and coexistence of underwater acoustic communication (UAC) networks, where linear frequency modulation (LFM) is a frame preamble signal commonly used for synchronization. Unlike terrestrial wireless communications, strong bursty noise frequently appears in UAC. Due to the long transmission distance and the low signal-to-noise ratio, strong short-distance bursty noise will greatly reduce the accuracy of conventional fractional fourier transform (FrFT) detection. We propose a multi-segment verification fractional fourier transform (MFrFT) preamble detection algorithm to address this challenge. In the proposed algorithm, 4 times of adjacent FrFT operations are carried out. And the LFM signal identifies by observing the linear correlation between two lines connected in pair among three adjacent peak points, called ‘dual-line-correlation mechanism’. The accurate starting time of the LFM signal can be found according to the peak frequency of the adjacent FrFT. More importantly, MFrFT do not result in an increase in computational complexity. Compared with the conventional FrFT detection method, experimental results show that the proposed algorithm can effectively distinguish between signal starting points and bursty noise with much lower error detection rate, which in turn minimizes the cost of retransmission.

This paper investigated a Subsample Time delay Estimation (STE) algorithm based on the amplitude of cross-correlation function to improve the estimation accuracy. In this paper, a rough time delay estimation is applied based on traditional cross correlator, and a fine estimation is achieved by approximating the sampled cross-correlation sequence to the amplitude of the theoretical cross-correlation function for linear frequency modulation (LFM) signal. Simulation results show that the proposed algorithm outperforms existing methods and can effectively improve time delay estimation accuracy with the complexity comparable to the traditional cross-correlation method. The theoretical Cramér-Rao Bound (CRB) is derived, and simulations demonstrate that the performance of STE can approach the boundary. Eventually, four important parameters discussed in the simulation to explore the impact on Mean Squared Error (MSE).

Since ISAR is widely applied in many occasions and provides high resolution images of the target, ISAR countermeasures are attracting more and more attention. Most of the present methods of deception jamming are not suitable for engineering realization due to the heavy computation load or the large calculation delay. Deception jamming against ISAR requires large computation resource and real-time performance algorithms. Many studies on false target jamming assume that the jammer is able to receive the target echo or transmit the jamming signal to the real target, which is sometimes not possible. How to impose the target property onto the intercepted radar signal is critical to a deception jammer. This paper proposes a jamming algorithm based on parallel convolution and one-bit quantization. The algorithm is able to produce a single false target on ISAR image by the jammer itself. The requirement for computation resource is within the capabilities of current digital signal processors such as FPGA or DSP. The method processes the samples of radar signal in parallel and generates the jamming signal at the rate of ADC data, solving the problem that the real-time performance is not satisfied when the input data rate for convolution is far higher than the clock frequency of FPGA. In order to reduce the computation load of convolution, one-bit quantization is utilized. The complex multiplication is implemented by logical resources, which significantly reduces the consumption of FPGA multipliers. The parallel convolution jamming signal, whose date rate exceeds the FPGA clock rate, is introduced and analyzed in detail. In theory, the bandwidth of jamming signal can be half of the sampling frequency of high speed ADC, making the proposed jamming algorithm able to counter ultra-wideband ISAR signals. The performance and validity of the proposed method are verified by simulations. This jamming method is real-time and capable of producing a false target of large size at the low cost of FPGA device.

This letter proposes a blind phase compensation method for the phase errors in the Multi-Carrier Multiple-input multiple-output (MIMO) radar, which decouples the range and DOA coupling. The phase errors under the Linear Frequency Modulated Continuous Waveform (LFMCW) scheme are firstly derived, followed with the signal processing steps. Further, multiple targets with certain velocities can be handled uniformly without pre-knowledge of the actual range information of the targets. The evaluations of the DOA estimation performance are carried out through simulations, which validate the effectiveness of the proposed method.

To improve detection performance for a reconnaissance receiver, which is designed to detect the non-cooperative MIMO-LFM radar signal under low SNR condition, this letter proposed a novel signal detection method. This method is based on Fractional Fourier Transform with entropy weight (FRFTE) and autocorrelation algorithm. In addition, the flow chart and feasibility of the proposed algorithm are analyzed. Finally, applying our method to Wigner Hough Transform (WHT), we demonstrate the superiority of this method by simulation results.

This paper presents a novel signal analysis algorithm, named High-order Bi-orthogonal Fourier Transform (HBFT), which can be seen as an expansion of Fourier transform. The HBFT formula and discrete HBFT formula are derived, some of their main characteristics are briefly discusses. This paper also uses HBFT to analyze the multi-LFM signals, obtain the modulate rate parameters, analyze the high dynamic signals, and obtain the accelerated and varying accelerated motion parameters. The result proves that HBFT is suitable for analysis of the non-stability signals with high-order components.

The combined linear frequency modulation continuous wave (LFMCW) and inverse synthetic aperture radar (ISAR) can be used for imaging long-distance targets because of its long-distance and high resolution imaging abilities. In this paper, we find and study the dechirp distortion phenomenon (DDP) for imaging long-distance targets by a dechirp-on-receive LFMCW radar. If the targets are very far from the radar, the maximum delay-time is not much smaller than a single sweep duration, and the dechirp distortion is triggered since the distance of the target is unknown in a LFMCW-ISAR system. DDP cannot be ignored in long-distance imaging because double images of a target appear in the frequency domain, which reduces resolution and degrades image quality. A novel LFMCW-ISAR signal model is established to analyze DDP and its negative effects on long-distance target imaging. Using the proportionately distributed energy of double images, the authors propose a method to correct dechirp distortion. In addition, the applicable scope of the proposed method is also discussed. Simulation results validate the theoretical analysis and the effectiveness of the proposed method.

This letter describe target classification from the synthesized active sonar returns from targets. A fractional Fourier transform is applied to the sonar returns to extract shape variation in the fractional Fourier domain depending on the highlight points and aspects of the target. With the proposed features, four different targets are classified using two neural network classifiers.

This letter deals with angular position classification using the synthesized active sonar returns from targets. For the synthesis of active sonar returns, we synthesized active sonar returns based on ray tracing algorithm for 3D highlight models. Then, a fractional Fourier transform (FrFT) was applied to the sonar returns to extract the angular position information depending on the target aspect by utilizing separation capability of the time-delayed combination of linear frequency modulated (LFM) signals in the FrFT domain. With the FrFT-based features, three different target angular positions were classified using neural networks.

We present a parallel multilevel fast multipole algorithm aimed at low cost parallel computers such as GRID computer environments and clusters of workstations. The algorithm is a scheduling algorithm where work packets are handled in a certain order to ensure minimal idle time of the processors and to avoid simultaneous bursts of communication between the processors. The algorithm is implemented on a method of moment discretization of a two-dimensional TM electromagnetic scattering problem. Examples of several optical devices with a size up to 28 500 wavelengths are presented.

We present a new method to detect weak linear frequency modulated (LFM) signals in strong noise using the chaos oscillator. Chaotic systems are sensitive to specific signals yet immune to noise. With our new method we firstly use the Radon-Wigner transform to dechirp the LFM signal. Secondly, we set up a chaotic oscillator sensitive to weak signals based on the Duffing equation, and poising the system at its critical state. Finally, we input the dechirped sequence into the system as a perturbation of the driving force. A weak signal with the same frequency will lead to a qualitative transition in the system state. The weak signal in the presence of strong noise can then be detected from the phase transition of the phase plane trajectory of the chaotic system. Computer simulation results show that LFM signals with an SNR lower than -27 dB can be detected by this method.

The effect of intermediate frequency magnetic fields or, very-low-frequency magnetic fields (VLFMF) on living biological cells was investigated using a highly sensitive mutagenesis assay method. A bacterial gene expression system for mutation repair (umu system) was used for the sensitive evaluation of damage in DNA molecules. Salmonella typhimurium TA1535 (pSK1002) were exposed to VLFMF (20 kHz and 600 µT) in a specially designed magnetic field loading chamber. The experiment results showed the possibility of applying the umu assay for sensitive and effective evaluation of damage in DNA molecules. No effects from exposure to 20 kHz and 600 µT magnetic fields in terms of damage in DNA molecules were observed.

In 1999, Boneh et al. proposed the Lattice Factoring Method (LFM) for the integer factoring problem for a composite of the form N = prq by employing the LLL-algorithm. Time complexity of LFM is measured by the number of calls of the LLL-algorithm. In the worst case, the number is 2log p for a certain constant c. In 2001, Uchiyama and Kanayama introduced a novel criterion and provided an improved algorithm which runs (2k-p)/|p-Nr+1| times faster (for certain constants k, Nr+1). In this letter, we note another practical improvement applicable to the original and the improved LFM, which enables to provide about 2 times speed-up.