Adaptive Radar Research Articles

АДАПТИВНОЕ ОБНАРУЖЕНИЕ СТАЦИОНАРНОГО ГАУССОВОГО СИГНАЛА НА ФОНЕ НОРМАЛЬНОГО ШУМА С ПОСТОЯННЫМ УРОВНЕМ ЛОЖНОЙ ТРЕВОГИ

PACS number: 84.40.Xb Purpose: Efficiency analysis of the Cell-Averaging Constant False Alarm Rate processor (CA CFAR-processor) as applied to detection of stationary Gaussian signals against a normal noise background with unknown and/or varying from scan to scan power. Design/methodology/approach: Standard methods of the theory of optimal filtration and statistical signal processing are used to calculate the true detection probability and false-alarm rate. Findings: Analytical expressions have been derived for the scaling factor which ensures a constant level of the false-alarm rate, as well as for the true detection probability in dependence on the number of the reference cells and signal-to-noise ratio. It is shown that for efficient application of the given algorithm, the number of the reference cells should be 20 to 30, depending on the signalto-noise ratio μ. In this case, the amount of loss in the signal-tonoise ratio does not exceed 1 to 2 dB as compared with the situation where the noise power is a priori known and invariable. With μ≥30 dB the amount of loss proves to be negligibly small and the need in adaptation vanishes. Conclusions: The results obtained testify to the efficiency of application of the CA CFAR processors to detection of targets corresponding to Swerling model 1 against a normal noise background with unknown power associated with clutter and/or scattering from irregularities of the propagation medium. Key words: target detection, false alarm rate, detection threshold, signal-to-noise ratio, cell averaging Manuscript submitted 26.06.2017 Radio phys. radio astron. 2017, 22(3): 231-237 REFERENCES 1. LEVIN, B. R., 1968. Theoretical fundamentals of statistical radio engineering, Volume 2. Moscow, USSR: Sov. Radio Publ. (in Russian). 2. KAY, S. M., 1998. Fundamentals of Statistical Signal Processing , Vol. II: Detection Theory. New Jersey: Prentice Hall. 3. BARTON, D. K., 1998. Modern Radar System Analysis . Boston, London: Artech House Books. 4. SKOLNIK, M. I., 2008. Radar Handbook . New York et al.: McGraw Hill Professional. 5. BAKULEV, P. A., BASISTOV, Y. A. and TUGUSHI, V. G., 1989. Signal processing with a constant false alarm rate. Izv. Vyssh. Uchebn. Zaved. Radioelektronika . vol. 32, no. 4, pp. 4 15 (in Russian). 6. HAYKIN, S., 2007. Adaptive Radar Signal Processing . New Jersey: John Wiley & Sons Inc. 7. EL MASHADE, M. B., 2014. Performance enhancement of conventional CFAR processors in ideal and multitarget environments. Radioelectron. Commun. Syst . vol. 57, is. 7, pp. 287 305. DOI: https://doi.org/10.3103/S0735272714070012 8. LONG CAI, XIAOCHUAN MA, QI XU, BIN LI and SHIWEI REN, 2011. Performance Analysis of Some New CFAR Detectors under Clutter. Journal of Computers . vol. 6, no. 6, pp. 1278 1285. DOI: https://doi.org/10.4304/jcp.6.6.1278-1285 9. FINN, H. M. and JOHNSON, R. S., 1968. Adaptive detection mode with threshold control as a function of spatially sampled clutter level estimates. RCA Rev . vol. 29, no. 3, pp. 414 464. 10. SWERLING, P., 1960. Probability of detection for fluctuating targets. IRE Trans. Inf. Theory. vol. 6, is. 2, pp. 269 308. DOI: https://doi.org/10.1109/TIT.1960.1057561 11. SIDOROV, Y. V., FEDORYUK, M. V. and SHABUNIN, M. I., 1989. Lectures on the theory of functions of complex variable . Moscow, USSR: Nauka Publ. (in Russian).

Amplifier-in-the-Loop Adaptive Radar Waveform Synthesis

Adaptive algorithms having the capacity to perform real-time optimization in response to a dynamic environment will be necessary for the development of a cognitive radar technology. This paper details an amplifier-in-the-loop algorithm to synthesize radar waveforms which are optimized for desired ambiguity function characteristics in a monostatic radar system, with constraints on the peak-to-average power ratio and spectrum of the waveform. The algorithm uses alternating projections to search for a waveform whose ambiguity function best approximates the goal for a volume-based constraint in desired regions of the range–Doppler plane. Results are shown for both simulation and measurement cases, both with and without the effects of a nonlinear amplifier. This waveform synthesis method is expected to be useful in real-time adaptive radar systems.

On the Statistical Invariance for Adaptive Radar Detection in Partially Homogeneous Disturbance Plus Structured Interference

This paper deals with the problem of adaptive vector subspace signal detection in partially homogeneous Gaussian disturbance and structured (unknown) deterministic interference within the framework of invariance theory. It is first proved that the Maximal Invariant Statistic (MIS) for the problem at hand is scalar-valued and coincides with the well-known adaptive normalized matched filter evaluated after data projection in the complementary subspace of the interfering signal. Second, the statistical characterization of the MIS under both hypotheses is derived. Then, it is shown the statistical equivalence of (two-step) generalized-likelihood ratio test, Rao and Wald tests, as well as the more recently considered Durbin and Gradient test, to the above statistic. Finally, simulation results are provided to confirm our findings and analyze the performance trend of the MIS with the relevant parameters.

On the Maximal Invariant Statistic for Adaptive Radar Detection in Partially Homogeneous Disturbance With Persymmetric Covariance

This letter deals with the problem of adaptive signal detection in partially-homogeneous and persymmetric Gaussian disturbance within the framework of invariance theory. First, a suitable group of transformations leaving the problem invariant is introduced and the Maximal Invariant Statistic (MIS) is derived. Then, it is shown that the (Two-step) Generalized-Likelihood Ratio test, Rao and Wald tests can be all expressed in terms of the MIS, thus proving that they all ensure a Constant False-Alarm Rate (CFAR).

Low probability of intercept-based adaptive radar waveform optimization in signal-dependent clutter for joint radar and cellular communication systems.

In this paper, we investigate the problem of low probability of intercept (LPI)-based adaptive radar waveform optimization in signal-dependent clutter for joint radar and cellular communication systems, where the radar system optimizes the transmitted waveform such that the interference caused to the cellular communication systems is strictly controlled. Assuming that the precise knowledge of the target spectra, the power spectral densities (PSDs) of signal-dependent clutters, the propagation losses of corresponding channels and the communication signals is known by the radar, three different LPI based criteria for radar waveform optimization are proposed to minimize the total transmitted power of the radar system by optimizing the multicarrier radar waveform with a predefined signal-to-interference-plus-noise ratio (SINR) constraint and a minimum required capacity for the cellular communication systems. These criteria differ in the way the communication signals scattered off the target are considered in the radar waveform design: (1) as useful energy, (2) as interference or (3) ignored altogether. The resulting problems are solved analytically and their solutions represent the optimum power allocation for each subcarrier in the multicarrier radar waveform. We show with numerical results that the LPI performance of the radar system can be significantly improved by exploiting the scattered echoes off the target due to cellular communication signals received at the radar receiver.

Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images.

We present preliminary results from a method for estimating the optimal effective permittivity for reconstructing microwave-radar images. Using knowledge of how microwave-radar images are formed, we identify characteristics that are typical of good images, and define a fitness function to measure the relative image quality. We build a polynomial interpolant of the fitness function in order to identify the most likely permittivity values of the tissue. To make the estimation process more efficient, the polynomial interpolant is constructed using a locally and dimensionally adaptive sampling method that is a novel combination of stochastic collocation and polynomial chaos. Examples, using a series of simulated, experimental and patient data collected using the Tissue Sensing Adaptive Radar system, which is under development at the University of Calgary, are presented. These examples show how, using our method, accurate images can be reconstructed starting with only a broad estimate of the permittivity range.

A Unifying Framework for Adaptive Radar Detection in Homogeneous Plus Structured Interference— Part I

This paper deals with the problem of adaptive multidimensional/multichannel signal detection in homogeneous Gaussian disturbance with unknown covariance matrix and structured deterministic interfer...

A Generalized Covariance Matrix Taper Model for KA-STAP in Knowledge-Aided Adaptive Radar

A Generalized Covariance Matrix Taper Model for KA-STAP in Knowledge-Aided Adaptive Radar

Design of LMS Adaptive Radar Detector for Non-homogeneous Interferences

ABSTRACTThe recent years have seen an unprecedented increase in the demand for superior performance of radar signal processor. The main challenge in a radar system is to maintain the probability of a false alarm rate constant even under an uncertain time-varying clutter environment. The objective of this paper is to develop a method for enhanced clutter/interference suppression by redesigning the radar detector in such a way to emphasize the target response and de-emphasize the clutter response. To achieve this, we have proposed a hardware architecture that implements least mean square algorithm-based adaptive filter along with a constant false alarm rate (CFAR) technique for the purpose of better detection of target under a non-homogeneous clutter environment. An adaptive design of the CFAR-filter technique has been used to improve probability of detection by increasing signal-to-noise ratio. The efficacy of the proposed architecture is corroborated with MATLAB simulations and hardware synthesis.

On the performance of a persymmetric adaptive matched filter

We examine the adaptive detection problem in the presence of colored noise with an unknown covariance matrix, by exploiting a persymmetric structure in the received signal. The persymmetric adaptive matched filter (PS-AMF) is used to address this problem, which can significantly alleviate the requirement of secondary data. In G. Pailloux et al. “Persymmetric adaptive radar detectors,” (2011) the probability of false alarm of the PS-AMF has been obtained in terms of the Gaussian hypergeometric function. In this paper, finite-sum expressions for the probability of false alarm of the PS-AMF are derived, which are more convenient to use in calculating the detection threshold. Moreover, the detection probabilities of the PS-AMF for both nonfluctuating and fluctuating target models are derived. In the fluctuating model, the amplitude of the target echoes is described by a generalized Chi distribution that involves the Rayleigh distribution as a special case. These theoretical results are all confirmed using Monte Carlo (MC) simulations.

Adaptive Radar Detection and Range Estimation with Oversampled Data for Partially Homogeneous Environment

In the present letter we investigate the problem of adaptive detection and range estimation for point-like targets buried in partially homogeneous Gaussian disturbance with unknown covariance matrix. To this end, we jointly exploit the spillover of target energy to consecutive range samples and the oversampling of the received signal. In this context, we design a detector relying on the Generalized Likelihood Ratio Test (GLRT). Remarkably, the new decision scheme ensures the Constant False Alarm Rate (CFAR) property with respect to the unknown disturbance parameters. The performance analysis reveals that it can provide enhanced detection performance compared with its state-of-art counterpart while retaining accurate estimation capabilities of the target position.

A Unifying Framework for Adaptive Radar Detection in Homogeneous Plus Structured Interference— Part I: On the Maximal Invariant Statistic

This paper deals with the problem of adaptive multidimensional/multichannel signal detection in homogeneous Gaussian disturbance with unknown covariance matrix and structured deterministic interference. The aforementioned problem corresponds to a generalization of the well-known Generalized Multivariate Analysis of Variance (GMANOVA). In this first part of the work, we formulate the considered problem in canonical form and, after identifying a desirable group of transformations for the considered hypothesis testing, we derive a Maximal Invariant Statistic (MIS) for the problem at hand. Furthermore, we provide the MIS distribution in the form of a stochastic representation. Finally, strong connections to the MIS obtained in the open literature in simpler scenarios are underlined.

A Unifying Framework for Adaptive Radar Detection in Homogeneous Plus Structured Interference— Part II: Detectors Design

This paper deals with the problem of adaptive multidimensional/multichannel signal detection in homogeneous Gaussian disturbance with unknown covariance matrix and structured (unknown) deterministic interference. The aforementioned problem extends the well-known Generalized Multivariate Analysis of Variance (GMANOVA) tackled in the open literature. In a companion paper, we have obtained the Maximal Invariant Statistic (MIS) for the problem under consideration, as an enabling tool for the design of suitable detectors which possess the Constant False-Alarm Rate (CFAR) property. Herein, we focus on the development of several theoretically-founded detectors for the problem under consideration. First, all the considered detectors are shown to be function of the MIS, thus proving their CFARness property. Secondly, coincidence or statistical equivalence among some of them in such a general signal model is proved. Thirdly, strong connections to well-known simpler scenarios found in adaptive detection literature are established. Finally, simulation results are provided for a comparison of the proposed receivers.

Adaptive Radar Beamforming for Interference Mitigation in Radar-Wireless Spectrum Sharing

The key to the feasibility of spectrum sharing between radar and wireless systems is effective mainlobe interference mitigation processing by the radar. Traditional array processing is capable to cancel sidelobe interferences only. This letter presents an innovative beamforming approach, the first of its kind, to eliminate wireless interference in both mainlobe and sidelobe directions based on a coherent phase-coding multiple-input multiple-output (MIMO) radar platform. The theoretical proof and conditions of simultaneous mainlobe interference cancellation and target detection using coherent MIMO radar are mathematically derived and numerically verified. The simulation results demonstrate the radar can effectively eliminate wireless interferences from base stations and mobile handsets during spectrum-sharing.

Target Detection in Low Grazing Angle with Adaptive OFDM Radar

Multipath effect is the main factor of deteriorating target detection performance in low grazing angle scenario, which results from reflections on the ground/sea surface. Amplitudes of the received signals fluctuate acutely due to the random phase variations of reflected signals along different paths; thereby the performances of target detection and tracking are heavily influenced. This paper deals with target detection in low grazing angle scenario with orthogonal frequency division multiplexing (OFDM) radar. Realistic physical and statistical effects are incorporated into the multipath propagation model. By taking advantage of multipath propagation that provides spatial diversity of radar system and frequency diversity of OFDM waveform, we derive a detection method based on generalized likelihood ratio test (GLRT). Then, we propose an algorithm to optimally design the transmitted subcarrier weights to improve the detection performance. Simulation results show that the detection performance can be improved due to the multipath effect and adaptive OFDM waveform design.

Real-time load impedance optimization for radar spectral mask compliance and power efficiency

This paper presents a fast optimization algorithm for power amplifiers in radar transmitters based upon a metric designed to assess spectral mask compliance. The search finds the load impedance maximizing the power-added efficiency (PAE) while providing compliance with the assigned spectral mask. Measurement results illustrate consistency in the chosen optimum values of efficiency, while spectral mask requirements are consistently met at the optimum load impedances chosen by the search. This algorithm will allow adaptive radar transmitter amplifiers to quickly adjust their load impedances to change frequency bands of operation, change spectral output properties based on nearby spectrum users, and meet dynamically varying spectral mask requirements.

Estimation of Sidelobe Level Variations of Phased Codes in Presence of Random Interference for Bistatic Wideband Noise Radar

We discuss the importance of using the sidelobe level of the cross-correlation function as a criterion to implement a noise radar based on the transmission of wideband binary waveforms. Theoretical expressions are introduced for the parameters Peak-Sidelobe, Secondary-Sidelobe, and Integrated-Sidelobe levels for both Golay and pseudorandom binary sequences in presence of additive white Gaussian noise, relating the sequence lengthMto the spectral powerN0of the interfering noise. These expressions offer a valuable method for adaptive radar waveform design in order to determine sequence requirements which allow facing the noise present in the frequency band of interest. We also show a comparison of the ambiguity functions for Golay and PRBS sequences to analyze their performance in terms of Doppler and range accuracy. We describe a practical implementation of a pseudonoise waveform-based bistatic radar with reduced sidelobe level due to the use of Golay codes in combination with single side band modulation and operation at UHF band. Experimental measurements were performed in actual scenarios for ranging test of single and double targets. Linear polarizations were combined with different length sequences to determine their influence on the sounder performance under field test conditions.

Direct algorithm for the Pareto load‐pull optimisation of power‐added efficiency and adjacent‐channel power ratio

Adaptive radar systems will be required to operate in different frequency bands with spectrum requirements that will likely change both in time and with geographic region. A new algorithm is presented that allows direct optimisation of an amplifier's load reflection coefficient to find a Pareto optimum between the power-added efficiency (PAE) and adjacent-channel power ratio. Comparisons of simulation and measurement results are presented. The new algorithm's results compare well with traditionally acquired data and show consistency between the optimum values for PAE that are obtained from different starting points. Measurement comparison is performed with the previous optimisation algorithm reported by the authors, and results show that up to a 50% reduction in the number of measured experimental queries can be obtained. This translates into a significant time savings in reconfiguring a radar transmitter power amplifier.

Adaptive Radar Sensitivity Time Control Based on Linear Prediction Sea Clutter

Sea clutter is interference background in radar target processing. It is difficult to detect long-range weak target in sea clutter. Sea clutter signal changes complex, with high intensity. For close signal, radar receiver will overload and reach saturation point. We are interested in the most dynamic range for displaying target echo and fast changing component of clutter. By analyzing spatial and temporal correlation of sea clutter, slow changing component can be minus from sea clutter. The innovation of this paper is to propose a linear prediction error method for sea clutter to increase dynamic range of radar receiver. It prevents overloading and reaching saturation point at close range.

Radar emitter signal recognition based on multi-scale wavelet entropy and feature weighting

In modern electromagnetic environment, radar emitter signal recognition is an important research topic. On the basis of multi-resolution wavelet analysis, an adaptive radar emitter signal recognition method based on multi-scale wavelet entropy feature extraction and feature weighting was proposed. With the only priori knowledge of signal to noise ratio (SNR), the method of extracting multi-scale wavelet entropy features of wavelet coefficients from different received signals were combined with calculating uneven weight factor and stability weight factor of the extracted multi-dimensional characteristics. Radar emitter signals of different modulation types and different parameters modulated were recognized through feature weighting and feature fusion. Theoretical analysis and simulation results show that the presented algorithm has a high recognition rate. Additionally, when the SNR is greater than -4 dB, the correct recognition rate is higher than 93%. Hence, the proposed algorithm has great application value.