Cosine Based Non-Linear Frequency Modulation Waveforms with Low Sidelobes

Suppression of sidelobes is critical in most radar applications. The sidelobes of around -30 dB to -60dB are of primary interest in several radar applications. Several studies focused on the design of Nonlinear frequency modulated (NLFM) waveforms. Two cosine-based NLFM waveforms, NLFM I and II, are designed and investigated for their performance for sidelobe level for different time-bandwidth (BT) products. The designed waveforms achieved sidelobe levels of about -65.25 dB and -79.42 dB at BT product 1000. For low BT product 50, the sidelobes achieved are -52.71 dB and -42.05 dB, respectively. The reduction in sidelobes increased with an increase in BT product. For overall performance, the designed waveforms were investigated for doppler tolerance and signal to noise ratio (SNR). An increase in SNR caused sidelobe levels to decrease. Like other NLFM waveforms, they exhibited doppler intolerance

FPGA based Identification of Frequency and Phase Modulated Signals by Time Domain Digital Techniques for ELINT Systems

In this paper, a decision tree algorithm based on time-domain digital technique is developed for the identification and classification of diverse radar intra-pulse modulated signals for the electronic intelligence system in real-time. This includes linear frequency modulation, non-linear frequency modulation, stepped frequency modulation and bi-phase modulation. The received signal is digitised and the instantaneous phase and high accuracy instantaneous frequency are estimated. The instantaneous amplitude is also estimated to get the start and stop of the pulse. Instantaneous parameters are estimated using a moving autocorrelation technique. The proposed algorithm is employed on the instantaneous frequency and the modulation is identified. The modulation type and modulation parameter are important for unique radar identification when similar radars are operating in a dense environment. Simulations are carried out at various SNR conditions and results are presented. The model for algorithm is developed using a system generator and implemented in FPGA. These results are compared when the proposed algorithm is used with the existing digital in-phase and quadrature-phase (DIQ) technique of instantaneous frequency and amplitude estimation

Waveform Design and Related Processing for Multiple Target Detection and Resolution

The performance of modern radar systems mostly depends on the radiated waveforms, whose design is the basis of the entire system design. Today’s coherent, solid-state radars (either of the phased array type or of the single-radiator type as air traffic control or marine radars) transmit a set of deterministic signals with relatively large duty cycles, an order of 10%, calling for pulse compression to get the required range resolution. Often, power budget calls for different pulse lengths (e.g., short, medium, and long waveforms with a rectangular envelope) to cover the whole radar range. The first part of the chapter includes the topic of mitigating the effect of unwanted side lobes, inherent to every pulse compression, which is achieved both by a careful and optimal design of the waveform and by a (possibly mismatched) suitable processing. The second part of the chapter deals with the novel noise radar technology, not yet used in commercial radar sets but promising: (1) to prevent radar interception and exploitation by an enemy part and (2) to limit the mutual interferences of nearby radars, as in the marine environment. In this case, the design includes a tailoring of a set of pseudo-random waveforms, generally by recursive processing, to comply with the system requirements

Adaptable Pulse Compression in φ-OTDR With Direct Digital Synthesis of Probe Waveforms and Rigorously Defined Nonlinear Chirping

Recent research in Phase-Sensitive Optical Time Doman Reflectometry (φ-OTDR) has been focused, among others, on performing spatially resolved measurements with various methods including the use of frequency modulated probes. However, conventional schemes either rely on phase-coded sequences, involve inflexible generation of the probe frequency modulation or mostly employ simple linear frequency modulated (LFM) pulses which suffer from elevated sidelobes introducing degradation in range resolution. In this contribution, we propose and experimentally demonstrate a novel φ-OTDR scheme which employs a readily adaptable Direct Digital Synthesis (DDS) of pulses with custom frequency modulation formats and demonstrate advanced optical pulse compression with a nonlinear frequency modulated (NLFM) waveform containing a complex, rigorously defined modulation law optimized for bandwidth-limited synthesis and sidelobe suppression. The proposed method offers high fidelity chirped waveforms, and when employed in resolving a 50-cm event at ∼1.13 km using a 1.2-μs probe pulse, matched filtering with the DDS-generated NLFM waveform results in a significant reduction in range ambiguity owing to autocorrelation sidelobe suppression of ∼20 dB with no averages and windowing functions, for an improvement of ∼16 dB compared to conventional linear chirping. Experimental results also show that the contribution of autocorrelation sidelobes to the power in the compressed backscattering responses around localized events is suppressed by up to ∼18 dB when advanced pulse compression with an optical NLFM pulse is employed

REAL-TIME ADAPTIVE PULSE COMPRESSION ON RECONFIGURABLE, SYSTEM-ON-CHIP (SOC) PLATFORMS

New radar applications need to perform complex algorithms and process a large quantity of data to generate useful information for the users. This situation has motivated the search for better processing solutions that include low-power high-performance processors, efficient algorithms, and high-speed interfaces. In this work, hardware implementation of adaptive pulse compression algorithms for real-time transceiver optimization is presented, and is based on a System-on-Chip architecture for reconfigurable hardware devices. This study also evaluates the performance of dedicated coprocessors as hardware accelerator units to speed up and improve the computation of computing-intensive tasks such matrix multiplication and matrix inversion, which are essential units to solve the covariance matrix. The tradeoffs between latency and hardware utilization are also presented. Moreover, the system architecture takes advantage of the embedded processor, which is interconnected with the logic resources through high-performance buses, to perform floating-point operations, control the processing blocks, and communicate with an external PC through a customized software interface. The overall system functionality is demonstrated and tested for real-time operations using a Ku-band testbed together with a low-cost channel emulator for different types of waveforms

Design and Optimization of Physical Waveform-Diverse and Spatially-Diverse Radar Emissions

With the advancement of arbitrary waveform generation techniques, new radar transmission modes can be designed via precise control of the waveform's time-domain signal structure. The finer degree of emission control for a waveform (or multiple waveforms via a digital array) presents an opportunity to reduce ambiguities in the estimation of parameters within the radar backscatter. While this freedom opens the door to new emission capabilities, one must still consider the practical attributes for radar waveform design. Constraints such as constant amplitude (to maintain sufficient power efficiency) and continuous phase (for spectral containment) are still considered prerequisites for high-powered radar waveforms. These criteria are also applicable to the design of multiple waveforms emitted from an antenna array in a multiple-input multiple-output (MIMO) mode. In this work, three spatially-diverse radar emission design methods are introduced that provide constant amplitude, spectrally-contained waveforms implemented via a digital array radar (DAR). The first design method, denoted as spatial modulation, designs the radar waveforms via a polyphase-coded frequency-modulated (PCFM) framework to steer the coherent mainbeam of the emission within a pulse. The second design method is an iterative scheme to generate waveforms that achieve a desired wideband and/or widebeam radar emission. However, a wideband and widebeam emission can place a portion of the emitted energy into what is known as the `invisible' space of the array, which is related to the storage of reactive power that can damage a radar transmitter. The proposed design method purposefully avoids this space and a quantity denoted as the Fractional Reactive Power (FRP) is defined to assess the quality of the result. The third design method produces simultaneous radar and communications beams in separate spatial directions while maintaining constant modulus by leveraging the orthogonal complement of the emitted directions. This orthogonal energy defines a trade-space between power efficiency gained from constraining waveforms to be constant amplitude and power efficiency lost by emitting energy in undesired directions. The design of FM waveforms via traditional gradient-based optimization methods is also considered. A waveform model is proposed that is a generalization of the PCFM implementation, denoted as coded-FM (CFM), which defines the phase of the waveform via a summation of weighted, predefined basis functions. Therefore, gradient-based methods can be used to minimize a given cost function with respect to a finite set of optimizable parameters. A generalized integrated sidelobe level (GISL) metric is used as the optimization cost function to minimize the correlation range sidelobes of the radar waveform. System specific waveform optimization is explored by incorporating the linear models of three different loopback configurations into the GISL metric to match the optimized waveforms to the particular systems

RADAR Signal Processing Using Multi-Objective Optimization Techniques

Pulse compression is used in radar system to achieve the range resolution of short duration pulses and Signal to Noise Ratio (SNR) of long duration pulses. Linear Frequency Modulated (LFM) pulse is one type of signal used in radar. In wide-band radar, for good range resolution, very wide bandwidth is used. The conventional hardware may not be able to sustain this large bandwidth. So the wideband signal is split into narrowband signals. In narrowband signals, frequency changes linearly for complete duration of the pulse. We change the center frequency of each LFM pulse by introducing a frequency step between consecutive pulses. The resultant signal is known as Stepped Frequency Pulse Train (SFPT). When the product of pulse duration and frequency step become more than one, the Autocorrelation Function (ACF) of SFPT yields undesirable peaks, known as grating lobes. Along with grating lobe, the higher peak side lobe can hides the small. Also the wide main lobe width deteriorate the range resolution capability of the signal. Many analytic techniques have been proposed in the literature to select the SFPT parameter to suppress the grating lobe, without paying much attention to side lobe and main lobe width. In this work we compare three MOO algorithms to find the optimized parameter of SFPT. The problem is studied in two ways: In first we take objective of minimization of grating lobes and peak side lobe level. The constraint is of increase in bandwidth. In second problem, our aim is to minimize the main lobe width, which improves the resolution. The objective functions for the second problem are minimization of main lobe width and peak side lobe level. We don’t want high grating lobe amplitude, so we add a constraint, which restrict the maximum grating lobe amplitude below a threshold value. Simulations are carried out for different range of parameter values and the simulation result shows the potential of the MOO approach

SAR processing with non-linear FM chirp waveforms.

Nonlinear FM (NLFM) waveforms offer a radar matched filter output with inherently low range sidelobes. This yields a 1-2 dB advantage in Signal-to-Noise Ratio over the output of a Linear FM (LFM) waveform with equivalent sidelobe filtering. This report presents details of processing NLFM waveforms in both range and Doppler dimensions, with special emphasis on compensating intra-pulse Doppler, often cited as a weakness of NLFM waveforms

The Atmospheric Imaging Radar for High Resolution Observations of Severe Weather

Mobile weather radars often utilize rapid scan strategies when collecting obser- vations of severe weather. Various techniques have been used to improve volume update times, including the use of agile and multi-beam radars. Imaging radars, similar in some respects to phased arrays, steer the radar beam in software, thus requiring no physical motion. In contrast to phased arrays, imaging radars gather data for an entire volume simultaneously within the field-of-view of the radar, which is defined by a broad transmit beam. As a result, imaging radars provide update rates significantly exceeding those of existing mobile radars, including phased arrays. The Atmospheric Radar Research Center at the University of Oklahoma is engaged in the design, construction and testing of a mobile imaging weather radar system called the Atmospheric Imaging Radar (AIR).Initial tests performed with the AIR demonstrate the benefits and versatility of utilizing beamforming techniques to achieve high spatial and temporal resolution. Specifically, point target analysis was performed using several digital beamform- ing techniques. Adaptive algorithms allow for the improved resolution and clutter rejection when compared to traditional techniques. Additional experiments were conducted during three severe weather events in Oklahoma, including an isolated cell event with high surface winds, a squall line, and a non-tornadic cyclone. Sev- eral digital beamforming techniques were tested and analyzed, producing unique, simultaneous multi-beam measurements using the AIR.The author made specific contributions to the field of radar meteorology in several areas. Overseeing the design and construction of the AIR was a signif- icant effort and involved the coordination of many smaller teams. Interacting with the members of each group and ensuring the success of the project was a primary focus throughout the venture. Meteorological imaging radars of the past have typically focused on boundary layer or upper atmospheric phenomena. The AIR's primary focus is to collect precipitation data from severe weather. Ap- plying well defined beamforming techniques, ranging from Fourier to adaptive algorithms like robust Capon and Amplitude and Phase Estimation (APES), to precipitation phenomena was a unique effort and has served to advance the use of adaptive array processing in radar meteorology. Exploration of irregular antenna spacing and drawing from the analogies between temporal and spatial process- ing led to the development of a technique that reduced the impact of grating lobes by unwrapping angular ambiguities. Ultimately, the author leaves having created a versatile platform capable of producing some of the highest resolution weather data available in the research community today, with opportunities to significantly advance the understanding of rapidly evolving weather phenomena and severe storms