High Resolution Sonar Signals in a Multipath Environment

Signal integration, as an effective method of detecting weak target, is widely used in areas of radar, sonar, etc. In previous studies of long-time coherent integration, researchers usually established a multi-pulse echo model with linear frequency modulation (LFM) signal due to its good compression performance and large Doppler tolerance. Then, perfect analytical formula can be deduced to compensate for range migration and Doppler spread, which is helpful in analyzing the mechanism of long-time coherent integration in depth. However, besides LFM, a wide variety of signal waveforms are also used in modern sonar and underwater guidance system to meet the requirements for diverse applications. For instance, continuous wave (CW) pulse is often used in signal detection, high resolution direction of arrival (DOA) estimation, and velocity estimation, while large time-bandwidth product waveforms such as modulated signal, coded signal, and pseudo-random signal are utilized for special tasks like anti-interference detection, channel matching, and active concealed detection. Therefore, the formulas and corresponding instructive conclusions deduced by LFM have no generality when other sonar waveforms are used in pulse integration. In this paper, we focus on long-time coherent integration for arbitrary signal reflected by underwater target moving with a uniform velocity and propose a motion-compensated coherent integration method for arbitrary complex envelop signal. A kind of general ambiguity function (GAF) for transmitted signal is defined to present a unified expression based on GAF for the output of the matched filter. The operation not only helps us to describe and calculate the pulse compression form of the arbitrary complex envelop by using a general mathematical model, but also provides information about the range migration and Doppler frequency shift of the multi-pulse echo, which is needed in pulse range alignment and FFT integration. For the matched filter output expressed by the GAF, Keystone transform is utilized to correct the complex envelop of the multi-pulse echo and eliminate the range walk. Then, Doppler frequency shift is compensated for by performing FFT transform, and the long-time coherent integration for arbitrary complex envelop is realized. To verify the correctness of the proposed method, we carry out the computer simulation on both signal integration and detection performance by using four sonar waveforms, i.e., CW signal, LFM signal, m-sequence phase-coded signal, and Costas frequency hop coded signal. The simulation results show that the proposed motion-compensated coherent integration method is applicable to arbitrary complex envelop signal. We also design an anechoic water tank experiment scheme which can successfully obtain the multi-pulse echoes of constant moving target. The motion-compensated coherent integration of the experimental data of the above-mentioned four waveforms further validates the effectiveness of the proposed method.

Automotive radar is an all-weather sensing technology that makes direct measurements of target motion thereby aiding in unmanned driving. Continuous-wave (CW) radars which use linear frequency modulation (FM) have been the most popular automotive sensing systems because of lower cost, higher range resolution, and lower transmit power than a pulse Doppler radar. The available spectrum for vehicular systems is limited and, therefore, avoiding mutual interference from multiple automotive radars operating in the same spectrum in a crowded traffic scenario is a major challenge. To address this, we present a Reduced bandwidth FMCW (ReMCW) radar that consumes less spectral resources without decreasing the range resolution and enables interference-free operation. Our CW radar waveform transmits few randomly chosen slopes within the original FMCW sweep. This waveform avoids range- Doppler coupling encountered in conventional FMCW radars. The parameters used for the design of this waveform conform to current automotive radar requirements. Numerical experiments with ReMCW show great savings in spectrum over the conventional FMCW radar.

Frequency diversity in linear frequency modulated (LFM) waveforms can introduce unintended range shifts among receive radars in a distributed environment. This can make it difficult to predict where interference will occur in those receive radars, particularly when multipath is considered. This paper introduces the concept of interference region in range-frequency space to characterize the interference levels at a receive radar caused by waveforms transmitted from different radars in a distributed architecture. Linear frequency modulated (LFM) stretch-processed waveforms provide wide bandwidth and high range resolution while imposing only modest demands on the digital processing capabilities of a radar system. For this reason they are the waveform family of choice for many current wideband radar systems, including synthetic aperture radar (SAR) systems. However, LFM waveforms do not easily lend themselves to applications that require orthogonality, such as distributed radar architectures. The widespread use of these waveforms and the processing advantages they provide make it worthwhile to examine schemes for their use in a distributed environment. The paper uses interference region analysis to assess the effectiveness of frequency diversity, upchirp-downchirp diversity and chirp slope mismatch using LFM stretch-processed waveforms in a distributed environment.

Future defence radar systems, and in particular the ballistic missile defence (BMD) application, demand radar with high resolution in both angle and range. The high resolution angle estimation requires a large antenna aperture of many wavelengths. The high range resolution requires a wideband waveform of several hundreds of MHz. This paper considers architectures and waveforms for wideband phased array radar and in particular the application of advanced digital adaptive beamforming. A typical wideband waveform used in this class of radar is linear frequency modulation (LFM). It is shown that this waveform is particularly well suited to digital adaptive beamforming. The large electrical aperture demands the use of time delay units for beamsteering, at least at subarray level. A new approach for digitally synthesising the time delay steering is presented. The importance of employing irregular (randomised) subarraying for time delay steering is presented to avoid the problem of wideband grating lobes. This is also a requirement of adaptive beamforming. Finally, an architecture for wideband digital adaptive beamforming which fits well with the use of LFM waveforms is presented.

A synthetic aperture radar (SAR) can produce high-resolution two-dimensional images of mapped areas. The SAR comprises a pulsed transmitter, an antenna, and a phase-coherent receiver. The SAR is borne by a constant velocity vehicle such as an aircraft or satellite, with the antenna beam axis oriented obliquely to the velocity vector. The image plane is defined by the velocity vector and antenna beam axis. The image orthogonal coordinates are range and cross range (azimuth). The amplitude and phase of the received signals are collected for the duration of an integration time after which the signal is processed. High range resolution is achieved by the use of wide bandwidth transmitted pulses. High azimuth resolution is achieved by focusing, with a signal processing technique, an extremely long antenna that is synthesized from the coherent phase history. The pulse repetition frequency of the SAR is constrained within bounds established by the geometry and signal ambiguity limits. SAR operation requires relative motion between radar and target. Nominal velocity values are assumed for signal processing and measurable deviations are used for error compensation. Residual uncertainties and high-order derivatives of the velocity which are difficult to compensate may cause image smearing, defocusing, and increased image sidelobes. The SAR transforms the ocean surface into numerous small cells, each with dimensions of range and azimuth resolution. An image of a cell can be produced provided the radar cross section of the cell is sufficiently large and the cell phase history is deterministic. Ocean waves evidently move sufficiently uniformly to produce SAR images which correlate well with optical photographs and visual observations. The relationship between SAR images and oceanic physical features is not completely understood, and more analyses and investigations are desired.

Underwater multi-targets tracking has always been a difficult problem in active sonar tracking systems. In order to estimate the parameters of time-varying multi-targets moving in underwater environments, based on the Bayesian filtering framework, the Random Finite Set (RFS) is introduced to multi-targets tracking, which not only avoids the problem of data association in multi-targets tracking, but also realizes the estimation of the target number and their states simultaneously. Usually, the conventional Probability Hypothesis Density (PHD) and Cardinalized Probability Hypothesis Density (CPHD) algorithms assume that the detection probability is known as a priori, which is not suitable in many applications. Some methods have been proposed to estimate the detection probability, but most assume that it is constant both in time and surveillance region. In this paper, we model the detection probability through the active sonar equation. When fixed the false detection probability, we can get the analytic expression for the detection probability, which is related to target position. In addition, this novel detection probability is used in PHD and CPHD algorithms and applied to underwater active sonar tracking systems. Also, we use the adaptive ellipse gate strategy to reduce the computational load in PHD and CPHD algorithms. Under the linear Gaussian assumption, the proposed detection probability is illustrated in both Gaussian Mixture Probability Hypothesis Density (GM-PHD) and Gaussian Mixture Cardinalized Probability Hypothesis Density (GM-CPHD), respectively. Simulation results show that the proposed Pd-GM-PHD and Pd-GM-CPHD algorithms are more realistic and accuratein underwater active sonar tracking systems.

Phased array ultrasonic total focusing method (TFM) imaging has attracted much attention due to its high detection image resolution and large dynamic range. However, due to the small emission energy of its single element, the echo signal is weak and susceptible to noise interference, resulting in a relatively low signal-to-noise ratio (SNR). Especially when detecting high sound attenuation carbon fiber reinforced polymer (CFRP) composites, the signal amplitude can decrease with depth to a level lower than the electronic noise introduced by the signal acquisition system. To solve this problem, a new imaging algorithm was proposed that combines the Golay code excitation using linear frequency modulation (LFM) signal as the carrier with the TFM algorithm (LFM-Golay TFM). Meanwhile, in order to further overcome the disadvantage of the LFM-Golay code encoding excitation method requiring two excitations, an AB code encoding excitation conversion factor was introduced, two sets of echo data were obtained through processing single excitation, TFM imaging based on LFM-Golay code single excitation (IMP-LFM-Golay TFM) is realized. Simulation and experimental studies were conducted to compare the TFM imaging performance of single-pulse excitation (Pulse TFM), Barker coding excitation (Barker TFM), LFM excitation (LFM TFM), and improved LFM-Golay coding excitation. The results show that IMP-LFM-Golay TFM has the best SNR, axial resolution, and depth resolution.

The pseudo-random binary-phase code phase modulation and linear frequency modulation (PN-LFM) combined ranging system is a new detection system, which has proven to be powerful capacity in range resolution, velocity resolution and maximum range measurable without ambiguity. In this paper, we study the anti-jamming performance of the new ranging system, especially in the fractal stochastic noise environments. We analyze the impact mechanism of fractal noise on the PN-LFM detection system, and simulate the output of correlating detection. The cross correlation function, power spectrum function and average power of pseudo random signal and fractal noise are deduced, compared with the impact of white noise on the pseudo code detection system. Simulation shows that PN-LFM combined ranging system possess powerful anti-jamming capacity, and performs better in the fractal noise environment than Pseudo random code phase modulation system.

Nonlinear frequency modulated excitation signal and modified compressing filter for improved range resolution and side lobe level of ultrasound echoes

The drag coefficient is a key parameter to quantify the wind stress over the ocean surface, which depends on the ocean surface roughness. During oil spill events, oil slicks cover the ocean surface and thus change the surface roughness by suppressing multi-scale ocean surface waves, and the drag coefficient is changed. This change has not been included in the current ocean circulation models. In this study, such change in sea surface roughness is studied by satellite remote sensing via synthetic aperture radar (SAR) data to quantify the changes in the wind effect over the oil-covered ocean surface. The concept of effective wind speed is introduced to quantify the wind work on the ocean. We investigate its influence on the wind-driven Ekman current at the ocean surface. Using observations from the Deepwater Horizon oil spill (2010) as an example, we find that the presence of oil can result in an effective wind speed of 50%~100% less than the conventional wind speed, causing overestimates by 75%~100% in the wind driven Ekman current. The effect of such bias on oil trajectory predictions is also discussed. Our results suggest that it is important to consider the effect of changes in the drag coefficient over oil-contaminated areas, especially for large-scale oil spill situations.

In this paper, a method for combining wideband and narrowband waveforms is proposed to improve target detection in shallow water environments. In this regard, a sonar waveform design suitable for target speed has been proposed too. The method uses a wideband frequency-modulated waveform for high range resolution in a reverberation environment and the Doppler-sensitive (DS) waveform to improve the detection of moving targets. The proposed combined waveform is mathematically modeled, and the Calculating of ambiguity function (AF) is performed. The AF and autocorrelation function (ACF) of the designed waveform indicate both DS and fair range resolution features simultaneously exist. So the initial range resolution for target detection is preserved. The Peak to Sidelobe level (PSL) ratio of the proposed waveform is at least 25 dB more than the previous state of the art waveforms. Calculating the Q-function criterion for the designed waveform reveals the superior reverberation suppression and detection performance with respect to the state of the art waveforms. After calculating the reverberation channel model, waveform echo, and detection of the target, the probability of detection (Pd) versus signal-to-reverberation ratio (SRR) was simulated by the Monte Carlo method. It was shown that the proposed waveform improved the probability of target detection by 20 dB, comparing to the base waveforms.

A pulsating bubble (and its image) beneath a flat pressure-release surface is equivalent to a dipole at the surface. Calculations of specular reflection of a source from a rough ocean surface predict that the curvature of the surface can have an important effect on the source directivity. Recent measurements of bubble concentrations indicate the presence of a low-velocity layer near the ocean surface, for frequencies below the bubble resonances. Estimates by Farmer et. al. [J. Acoust. Soc. Am. 86, 1897–1908 (1989)] give a maximum velocity deficit of Δc≈18.3 m/s at 5 kHz, for wind velocities 12–14 m/s. This gives an index of refraction just less than unity, n≈.99. The relative effects of refraction near the ocean surface, attenuation and the curvature of the rough surface on the source directivity are calculated. It is found that the effects of the curvature of the ocean surface can dominant refraction and attenuation.

High Range Resolution (HRR) -based Automatic Target Recognition (ATR) has attracted increasing attention due to a number of potential advantages over alternative radar techniques in moving target identification. Most current HRR-based ATR studies have been conducted using 1D HRR signatures. However, these 1D HRR signatures are generally plagued by scintillation effects, and thus demonstrate highly irregular behavior that dramatically degrades the performance and robustness of algorithms based on these signatures. In order to circumvent this difficulty, an alternative HRR radar data representation and processing technique is presented in this paper. This technique models and extracts the target characteristics directly, based on the 2D HRR raw data. In this paper, we first derive a general, but complex HRR radar model, and then simplify this model by instantiating a set of real-world radar and target parameters for the model. This simplification process produces two HRR radar models with different degrees of simplicity. After establishing this set of models, the typical HRR data processes, such as feature extraction and clutter suppression, are reduced to one problem, which is model-parameter estimation. Based upon the most simplified HRR model we proposed, we devise two model- parameter estimation algorithms. One is a scatterer extraction algorithm based on available 1D Parameter Estimation (1DPE), while the other is based on 2D discrete Fourier Transform (2DFT). In order to examine the performance of these two algorithms a set of simulations are conducted. The experimental results are presented, and the performance comparison between 1DPE and 2DFT is presented.

The most important radar system performance is determining the range-velocity of the detected target. This performance is obtained from processing an ambiguity-function (AF) between signals from target reflections and radar radiation signals. Selection of the appropriate waveform transmitted by the radar is a key factor in supporting high resolution radar performance in the AF. There are many waveforms that have been studied in radar systems, especially for multi-antenna radars, i.e., subarray-MIMO (SMIMO) radar which can form phased array (PA) and MIMO radars simultaneously, in the form of linear-frequency-modulated (LFM) signals. In this paper, we examine the use of LFM waveforms combined with SMIMO radar to produce plots of three-dimensional AF as a function of time delay and Doppler shift. The results of the comparison with the Hadamard signal determine the effectiveness of the observed AF performance on parameters such as magnitude, range-velocity resolution, peak sidelobe level ratio, and integrated sidelobe ratio by taking into account the factors of the number of Tx antennas on the PA radar and the number of Tx subarrays on the MIMO radar. The evaluation results of the SMIMO radar configuration (M = 6) with the number of Tx-Rx antenna elements the being 8 provide the best mainlobe magnitude, sidelobe magnitude, range resolution, velocity resolution, PSLR, and ISLR of AF LFM signals compared to conventional radars are 235.2dB, 7.54dB, 37.5m, 75km/s, 29.89dB, and 29.8dB, respectively. Meanwhile, the LFM signal is far superior to the Hadamard signal which has PSLR and ISLR 1.16dB and -3.36dB, respectively.

Radar system uses Pulse compression techniques to provide the benefits of larger range detection and high range resolution. The transmitted signal undergoes modulation to obtain this and after that matching is carried out with the echo signal (received signal) and transmitted signal. In the past several pulse compression techniques are used, out of which the well known method is linear frequency modulation (LFM). This paper deals with the design to develop and simulate pulse compression and matched filter algorithm in MATLAB to study the LFM pulse compression technique. Matched filter is used as the pulse compression filter which provides high SNR at the output. Matched Filter is mathematically equivalent to convolving the received signal with a conjugated time-reversed version of the reference signal. The main application of pulse compression Radars includes tracking of launch vehicles, abdicable components in space, Missile guidance etc. Here, in this paper we are discussing the pulse compression application in tracking the launch vehicle so as to check whether it had followed the predetermined path or not.