Random Noise Waveforms Research Articles

Comparison of noise and chirp waveforms for radar target detection in clutter

The use of random noise waveforms is investigated for radar surveillance and their performance is compared with traditional chirp waveforms based on the correlation and relative ratio of received to transmitted powers after reflections from simple targets and terrain. For simple shapes, the correlation of the two signals was similar in value and pattern with respect to the incidence angle. The reflection from terrain clutter gave smaller correlations for the noise waveform indicating that it may be less susceptible to false alarms. Additional simulations were performed for a hummer vehicle target using terrain clutter models to create receiver operating characteristic curves. It was found that the noise waveform performs as well as the chirp for cases of strong clutter response, and much better for cases of weak clutter response.

Linear‐FM random radar waveform compressed by dechirping method

This research proposes a novel linear frequency modulation (Linear-FM) random radar waveform and introduces a dechirping compression method. The proposed linear-FM random waveforms possess a thumbtack ambiguity function and low cross-correlation properties which are good for fighting against digital radio frequency memory repeat jammer similar to random noise waveforms. The dechirping compression method for the proposed linear-FM random radar waveform works by mixing the random radar echo signal with a local reference linear frequency modulated (LFM) signal to reduce the echo bandwidth and thus allows to use low-speed analogue-to-digital converter similar to the dechirping method for LFM waveform compression. Both numerical simulation and high-resolution circular synthetic aperture radar imaging experiment are conducted to demonstrate the good performance of the proposed waveform and the proposed dechirping compression method.

Корреляционная оценка при передаче информации относительным методом на основе широкополосных шумовых сигналов.

Корреляционная оценка при передаче информации относительным методом на основе широкополосных шумовых сигналов.

Waveform design with low range sidelobe and high Doppler tolerance for cognitive radar

This paper considers the unimodular Linear-FM Synthesized (LFM-Syn) waveform design for cognitive radar.Firstly, the synthesized waveform is formulated by a given phase-scaling factor which combines the random noise waveform and the conventional LFM waveform. Secondly, to achieve low range sidelobes and high Doppler tolerance of LFM-Syn waveforms, a novel template-optimizing objective function is established and then transformed into a two-variable non-convex optimization case with constraints on quadratic phase and random phase. Meanwhile, a Relaxed Alternating Projection Phase Control method (RAPPC) incorporating spectrum approximation relaxed alternating projection and quadratic phase amendment is proposed via an iterative way. RAPPC not only enhances local exploiting for desired waveforms but also keeps high Doppler tolerance and low range sidelobes. Lastly, simulations have provided evidences that the LFM-Syn waveform optimized by RAPPC 1) has high Doppler tolerance similar to conventional LFM, 2) has Low Probability of Intercept (LPI) similar to random noise waveform, and 3) has low range sidelobe levels for prescribed requirement. Additionally, simulations also highlight the superior performance of our proposed algorithms over several existing techniques.

Ultrawideband Noise Radar Imaging of Impenetrable Cylindrical Objects Using Diffraction Tomography

Ultrawideband (UWB) waveforms achieve excellent spatial resolution for better characterization of targets in tomographic imaging applications compared to narrowband waveforms. In this paper, two-dimensional tomographic images of multiple scattering objects are successfully obtained using the diffraction tomography approach by transmitting multiple independent and identically distributed (iid) UWB random noise waveforms. The feasibility of using a random noise waveform for tomography is investigated by formulating a white Gaussian noise (WGN) model using spectral estimation. The analytical formulation of object image formation using random noise waveforms is established based on the backward scattering, and several numerical diffraction tomography simulations are performed in the spatial frequency domain to validate the analytical results by reconstructing the tomographic images of scattering objects. The final image of the object based on multiple transmitted noise waveforms is reconstructed by averaging individually formed images which compares very well with the image created using the traditional Gaussian pulse. Pixel difference-based measure is used to analyze and estimate the image quality of the final reconstructed tomographic image under various signal-to-noise ratio (SNR) conditions. Also, preliminary experiment setup and measurement results are presented to assess the validation of simulation results.

Passive localization of noise-producing targets using a compact volumetric array.

A technique is presented for passively localizing multiple noise-producing targets by cross-correlating the elevation beams of a compact volumetric array on separate bearings. A target's multipath structure inherently contains information about its range; however, unknown, random noise waveforms make time separation of individual arrivals difficult. Ocean ambient noise has previously been used to measure multipath delays to the seabed by cross-correlating the beams of a vertical line array [Siderius, Song, Gerstoft, Hodgkiss, Hursky, and Harrison, J. Acoust. Soc. Am. 127, 2193-2200 (2010)], but this methodology has not been applied to distant noise sources having non-vertical arrivals. The technique presented in this paper uses a compact volumetric array mounted to an autonomous underwater vehicle to measure the three-dimensional directionality and time delays of multipath arrivals, while adaptively rejecting clutter and multi-target interference. This is validated with experimental results in a shallow ocean environment in which a small workboat maneuvered in the vicinity. Short ranges could be estimated reliably using straight ray paths, but longer ranges required accounting for ray refraction.

Passive multi-target localization by cross-correlating beams of a compact volumetric array

A technique is presented for passively localizing multiple noise-producing targets by cross-correlating the elevation beams of a compact volumetric array on separate bearings. A target's multipath structure inherently contains information about its range, however unknown, random noise waveforms make time separation of individual arrivals difficult. Ocean ambient noise has previously been used to measure multipath delays to the seabed by cross-correlating the beams of a vertical line array [Siderius et al., J. Acoust. Soc. Am. 127, 2193–2200 (2010)], but this methodology has not been applied to distant noise sources having non-vertical arrivals. In this paper, methods are presented for using a compact volumetric array mounted to an autonomous underwater vehicle to measure the directionality and time delays of multipath arrivals, while simultaneously rejecting clutter and interference. This is validated with results from the GLASS'12 experiment in which a small workboat maneuvered in shallow water. Short ranges could be estimated reliably using straight ray paths, but longer ranges required accounting for ray refraction effects. Further, this is related to striation patterns observed in spectrograms, and it is shown that measured multipath time delays are used to predict this pattern, as well as the waveguide invariant parameter, β.

Waveform design for compressively sampled ultrawideband radar

Compressive sensing makes it possible to recover sparse target scenes from under-sampled measurements when uncorrelated random-noise waveforms are used as probing signals. The mathematical theory behind this assertion is based on the fact that Toeplitz and circulant random matrices generated from independent identically distributed (i.i.d) Gaussian random sequences satisfy the restricted isometry property. In real systems, waveforms have smooth, nonideal autocorrelation functions, thereby degrading the performance of compressive sensing algorithms. Compressive sensing requires the system matrix to have particular properties. Incorporating prior information into the target scene either to enhance imaging or to mitigate nonidealities can result in system matrices that are not suitable for compressive sensing. We can overcome this problem by designing appropriate transmit waveforms. We extend the existing theory to incorporate such nonidealities into the analysis of compressive recovery. As an example we consider the problem of tailoring waveforms to image extended targets. Extended targets make the target scene denser, causing random transmit waveforms to be suboptimal for recovery. We propose to incorporate extended targets by considering them to be sparsely representable in redundant dictionaries. We demonstrate that a low complexity algorithm to optimize the transmit waveform leads to improved performance.

Range-Doppler Resolution of the Linear-FM Noise Radar Waveform

This research considers the linear-FM (LFM) of a noise radar waveform for resolving targets when channel noise and four popular radar sidelobe weighting functions are considered. By using large time-bandwidth products and systematically varying the phase scaling factor κ, results from the digital matched filter output provide evidence that the LFM noise waveform 1) has range-Doppler resolution similar to conventional chirp waveforms and 2) has a low probability of intercept (LPI) similar to random noise waveforms. We acquire the results using a computer-based simulation and verify the location of target peaks using the chirp waveform output for both stationary and moving target cases.

Efficient seismic forward modeling using simultaneous random sources and sparsity

The high cost of simulating densely sampled seismic forward modeling data arises from activating sources one at a time in sequence. To increase efficiency, one could leverage recent innovations in seismic field-data acquisition and activate several (e.g., 2–6) sources simultaneously during modeling. However, such approaches would suffer from degraded data quality because of the interference between the model’s responses to the simultaneous sources. Two new efficient simultaneous-source modeling approaches are proposed that rely on the novel tandem use of randomness and sparsity to construct almost noise-free model response to individual sources. In each approach, the first step is to measure the model’s cumulative response with all sources activated simultaneously using randomly scaled band-limited impulses or continuous band-limited random-noise waveforms. In the second step, the model response to each individual sourceis estimated from the cumulative receiver measurement by exploiting knowledge of the random source waveforms and the sparsity of the model response to individual sources in a known transform domain (e.g., curvelet domain). The efficiency achievable by the approaches is primarily governed by the sparsity of the model response. By invoking results from the field of compressive sensing, theoretical bounds are provided that assert that the approaches would need less modeling time for sparser (i.e., simpler or more structured) model responses. A simulated modeling example is illustrated that shows that data collected with as many as 8192 sources activated simultaneously can be separated into the 8192 individual source gathers with data quality comparable to that obtained when the sources were activated sequentially. The proposed approaches could also dramatically improve seismic field-data acquisition efficiency if the source signatures actually probing the earth can be measured accurately.

Implementation of fully polarimetric random noise radar

A heterodyne correlation receiver technique has been developed for coherent processing of backscatter data acquired by a radar system transmitting ultrawideband (UWB) random noise waveforms. In such a receiver, the reflected signal is correlated with a time-delayed and frequency-shifted version of the transmitted waveform, which is able to provide the phase of the reflected waveform. We describe the implementation of fully polarimetric capability in a coherent random noise radar system operating in the ultrahigh frequency (UHF) range designed for foliage penetration (FOPEN) applications. Using this implementation, the polarimetric response of various foliage targets has been characterized.

Noise radar using random phase and frequency modulation

Pulse compression radar is used in a great number of applications. Excellent range resolution and high electronic counter-countermeasures performance is achieved by wideband long pulses, which spread out the transmitted energy in frequency and time. By using a random noise waveform, the range ambiguity is suppressed as well. In most applications, the random signal is transmitted directly from a noise-generating microwave source. A sine wave, which is phase or frequency modulated by random noise, is an alternative, and in this paper, the ambiguity function and the statistical characteristics of the correlation output for the latter configuration are further analyzed. Range resolution is then improved because the noise bandwidth of the modulated carrier is wider than that of the modulating signal, and the range sidelobes are also further suppressed. Random biphase modulation gives a 4-dB (/spl pi//sup 2//4) improvement, but much higher sidelobe suppression could be achieved using continuous phase/frequency modulation. Due to the randomness of the waveform, the output correlation integral is accompanied by a noise floor, which limits the possible sidelobe suppression as determined by the time-bandwidth product. In synthetic aperture radar (SAR) applications with distributed targets, this product should be large compared with the number of resolution elements inside the antenna main beam. The advantages of low range sidelobes and enhanced range resolution make frequency/phase-modulated noise radar attractive for many applications, including SAR mapping, surveillance, altimetry, and scatterometry. Computer algorithms for reference signal delay and compression are discussed as replacements for the classical delay line implementation.

Acoustooptic Correlation Processing in Random Noise Radar

A new technique has been developed that permits coherent processing of backscatter data acquired by a radar system transmitting ultrawideband (UWB) random noise waveforms and processing the received signals using a heterodyne correlation receiver. This technique has been used in various applications, such as Doppler estimation, polarimetry, interferometry, buried-object detection, synthetic aperture radar (SAR) imaging, inverse SAR (ISAR) imaging, foliage penetration imaging, etc. One of the major advantages of the noise radar system is its inherent immunity to external interference. In such a radar system, the correlation receiver consists of a programmable variable-delay line, a mixer followed by a lowpass filter. One drawback of this type of receiver is that it sequentially processes the target returns, thus limiting the system response time and the dynamic detection range. We have recently integrated a novel heterodyning acoustooptic (AO) time-integrating correlation receiver that uses a traveling-wave AO deflector for wideband signal processing. The transmit waveform modulates the intensity of a laser diode that is multiplied by the traveling-wave modulation produced by the AO deflector, and the correlation is time-integrated on a charge-coupled device photodetector array. The principal advantages of this AO correlation receiver are its ability to generate a large range of variable delays, as well as to perform the signal correlation operation in parallel. Compared to the conventional sequential correlation receiver using a variable stepped delay line and correlator, implementation of the AO variable-delay line and heterodyning correlator can 1) reduce the processing time and greatly increase the processing gain due to the parallel correlation mechanism and 2) greatly increase the number of range cells depending on the number of resolvable spots of the AO deflector. This results in rapid data acquisition, longer integration time on parallel detector pixels (3000 pixels), and improved SNR. It is also shown that this radar has more range gates (up to 1000), which ultimately improves the detectable range resolution. Furthermore, several field experiments performed with different target arrangements demonstrate that the acoustooptic variable-delay line and correlator is able to profile various targets instantaneously and with very high SNR.

Radar penetration imaging using ultra-wideband (UWB) random noise waveforms

Ultra-wideband (UWB) radar has been proven to be a very powerful tool for high-resolution penetration imaging of obscured objects. The authors discuss a radar penetration imaging technique using UWB random noise waveforms. The theoretical foundations for random noise radar, the random noise radar imaging model, and the synthetic aperture radar (SAR) image formation algorithm are presented. Typical field test results using an experimental random noise radar system are demonstrated.

Monte Carlo based time-domain Hspice noise simulation for CSA-CRRC circuit

We present a time-domain Monte Carlo based Hspice noise simulation for a charge-sensitive preamplifier-CRRC (CSA-CRRC) circuit with random amplitude piecewise noise waveform. The amplitude distribution of thermal noise is modeled with Gaussian random number. For 1/f noise, its amplitude distribution is modeled with several low-pass filters with thermal noise generators. These time-domain noise sources are connected in parallel with the drain and source nodes of the CMOS input transistor of CSA. The Hspice simulation of the CSA-CRRC circuit with these noise sources yielded ENC values at the output node of the shaper for thermal and 1/f noise of 47e− and 732e−, respectively. ENC values calculated from the frequency-domain transfer function and its integration are 44e− and 882e−, respectively. The values for Hspice simulation are similar to those for frequency-domain calculation. A test chip was designed and fabricated for this study. The measured ENC value was 904e−. This study shows that the time-domain noise modeling is valid and the transient Hspice noise simulation can be an effective tool for low-noise circuit design.

Generalised wideband ambiguity function of a coherent ultrawideband random noise radar

A coherent ultrawideband (UWB) random noise radar system has been developed and field tested at the University of Nebraska–Lincoln (UNL). A heterodyne correlation technique based on a time-delayed and frequency-shifted replica of the transmit waveform is used to inject coherence within this system. The radar's combined range and range rate resolution characteristics were investigated using the generalised wideband ambiguity function. As in the narrowband random noise waveform case, range and range rate resolutions can be controlled independently, the former being inversely related to the transmit bandwidth, while the latter is inversely related to the bandwidth of the integrating filter. It is also shown that UWB waveforms are not suitable for accurate range rate estimation due to the extended Doppler-spread parameter, i.e. the product of the transmit bandwidth and the target range rate, unless the correlator is matched in the delay rate as well.

ECCM capabilities of an ultrawideband bandlimited random noise imaging radar

Investigated here is high-resolution imaging of targets in noisy or unfriendly radar environments through a simulation analysis of the ultrawideband (UWB) continuous-wave (CW) bandlimited random noise waveform. The linear FM chirp signal was selected as a benchmark radar waveform for comparison purposes. Simulation of the recovery of various types of target reflectivity functions (TRFs) for these waveforms were performed and analyzed. In addition, electronic counter-countermeasure (ECCM) capabilities for both types of systems were investigated. The results are compared using the error between the interference (jamming)-free recovered TRF and the recovered TRF under noisy conditions as a function of the signal-to-interference/jamming ratio (SIR/SJR). Our analysis shows that noise waveforms possess better jamming immunity (of the order of 5-10 dB improvement over the linear FM chirp) due to the unique radar correlation processing in the receiver.

FOPEN SAR imaging using UWB step-frequency and random noise waveforms

The detection and identification of targets obscured by foliage have been topics of great interest. Several synthetic aperture radar (SAR) experiments have demonstrated promising images of terrain and man-made objects obscured by dense foliage, by using either linear frequency modulation (LFM) or step-frequency waveforms. We present here the methodology and results of a comparative study on foliage penetration (FOPEN) SAR imaging using ultrawideband (UWB) step-frequency and random noise waveforms. A statistical-physical foliage transmission model is developed for simulation applications. The foliage obscuring pattern is analyzed by means of the technique of paired echoes. The results of the comparative study demonstrates the ability of a UHF band UWB random noise radar to be used as a FOPEN SAR. Advantages of the random noise radar system include covert detection and immunity to radio frequency interference (RFI).

Time-domain thermal noise simulation of switched capacitor circuits and delta-sigma modulators

This paper presents an accurate and efficient algorithm for simulating the effects of thermal noise in time-domain. The algorithm presented in this paper is based on Monte Carlo methods and is applicable to linear time invariant circuits. In addition to linear time invariant elements, the algorithm can easily be extended to include clock controlled switches and single or multibit quantizers. This expands the thermal noise analysis capability to switched capacitor circuits and oversampled delta-sigma modulators. Thermal noise generated by different elements is modeled, in the time-domain, by a random pulse waveform having a desired power spectral density. Typically the noise power level is much smaller than that of other desired signals in the circuit and accurate simulation is needed to obtain correct results. In addition, random noise waveforms require the computation of many time points in each transient analysis and efficient simulation methods are needed. In this paper, a new method for computing the transient response of linear time invariant circuits is used. This method accurately and efficiently computes the response to the random pulse waveforms. In addition to thermal noise, the method can also be used to simulate the effect of random dither signals in delta-sigma modulators. Examples of noise simulation are given and, when possible, comparison with measurements, previously published results, or analytical expressions is done.