Weight effects on the periodic ambiguity function

CW radar signals and processors are discussed. The use of the periodic ambiguity function (PAF) to analyze the delay-Doppler performance of CW signals and their corresponding correlation receivers, is extended to include weight function effects. This work provides tools which can predict the delay-Doppler response of almost any phase-coded CW radar. Examples demonstrate that a combination of CW signals having perfect periodic autocorrelation, a matched reference signal with a large number of modulation periods and a smooth weight function, can create a delay-Doppler response with extremely low sidelobes, strongly resembling the response of a coherent pulse train     

Two-valued frequency-coded waveforms with favorable periodic autocorrelation

There are known phase-coded (two-valued or polyphase) CW radar signals that exhibit perfect periodic autocorrelation function (PACF). A PACF is perfect when all its out-of-phase autocorrelation values are identically equal to zero. This paper investigates periodic, two-valued, frequency-coded signals. While none could be found with perfect PACF, we present examples with nearly perfect PACF. Their relationship to binary phase-coded signals is also considered. These signals should be attractive for CW radars because of their simple implementation, clean spectrum, and the favorable range response of their matched receiver.     

Periodic ambiguity function of CW signals with perfect periodicautocorrelation

A periodic ambiguity function (PAF) is discussed which describes the response of a correlation receiver to a CW signal modulated by a periodic waveform, when the reference signal in the receiver is constructed from an integral number N, of periods T, of the transmitted signal. The PAF is a generalization of the periodic autocorrelation function, to the case of non-zero Doppler shift. It is shown that the PAF of N periods is obtained by multiplying the PAF of a single period by the universal function sin(Nπν T)/N sin(πνT), where ν is the Doppler shift, to phase-modulated signals which exhibit perfect periodic autocorrelation when there is no Doppler shift. The PAF of these signals exhibits universal cuts along the delay and Doppler axes. These cuts are functions only of t, N and the number M, the modulation bits in one period     

Reciprocal radar waveforms

Digitally coded radar waveforms can be used to obtain large time-bandwidth products (pulse compression ratios). It is demonstrated that periodic radar waveforms with zero sidelobes or almost zero sidelobes can be defined. A perfect periodic code is a periodic code whose autocorrelation function has zero sidelobes and whose amplitude is uniform (maximum power efficiency=1). An asymptotically perfect periodic code has the property that as the number of elements in the code goes to infinity the autocorrelation function of the code has zero sidelobes and its power efficiency is one. The authors introduce a class of radar waveforms that are either perfect or asymptotically perfect codes. These are called reciprocal codes because they can be derived through a linear transformation of known codes. The aperiodic performance of the reciprocal code is examined     

Design and analysis of new p(n,k) polyphase pulse compression codes

P(n,k) codes as a new class of polyphase pulse compression codes are introduced and analyzed in detail. The P(n,k) codes are conceptually derived by step approximation of the phase function of a nonlinear-frequency modulated (NLFM) Chirp signal with a favorable energy density spectrum. The significant advantages of P(n,k) codes over conventional polyphase codes are lower autocorrelation sidelobes and an improved tolerance of low Doppler shifts and precompression bandwidth limitations. The primary disadvantage of the P(n,k) codes over conventional codes is a loss in range resolution. The uniform P(n,k) codes are especially attractive for radars employing digital signal professing because their favorable correlation properties also remain when quantization effects are taken into account     

Mismatched filtering of odd-periodic binary sequences

Binary sequences with perfect periodic autocorrelation functions, as required in communications, radar, and measuring, are not known for any lengths >4. As a possible remedy, mismatched filtering can be used to entirely suppress any sidelobes of the periodic autocorrelation function at the expense of a reduced signal-to-noise ratio (SNR). In this work, the mismatched filtering method is extended to the odd-periodic autocorrelation function whose technical implementation is no more complex than that of periodic sequences. A new class of odd-periodic binary sequences is constructed that exist for many more lengths and exhibit significantly lower mismatched filtering losses than any known periodic sequences     

CW alternatives to the coherent pulse train-signals and processors

Continuous wave (CW) signals phase modulated by a periodic waveform, and their corresponding receivers, are discussed. The combined response in delay and Doppler is almost identical to the (ideal) response of the coherent pulse train. The receivers are matched to an integral number N of modulation periods of the transmitted signal. CW implies a duty cycle of 100%. However, the signal duration need not be longer than N+2 periods. The CW signals have the advantage that their peak power is equal to the average power. Their disadvantages are more complicated receiver processing and the need for two antennas     

Probablity of Detection for ICW Radars

Eclipsing of received signals is analyzed for Interrupted Continuous Wave (ICW) radars. A probability density for the Signal to Noise Ratio (SNR) at the Doppler filter output is derived which incorporates eclipsing effects and a fluctuating target cross section model. The probability of detection as a function of SNR is calculated for typical ICW parameters and the magnitude of the detection loss due to eclipsing is assessed     

Sequences and arrays with perfect periodic correlation

Properties and methods for synthesizing sequences with perfect periodic autocorrelation functions and good energy efficiency are discussed. The construction is extended to two-dimensional perfect arrays. The construction methods used are based mainly on a search in the frequency domain and on a multiplication theorem for periodic sequences and arrays     

BOC信号自适应门限判决捕获方法

BOC信号是一种分离频谱的调制方式,与传统的导航扩频信号相比,具有更强的抗干扰能力和更高的测量精度。但BOC信号自相关函数具有多峰值的特点,如何从接收端找出最大峰值并正确恢复BOC信号是技术难点。本文给出了一种BOC信号的捕获方案和具体的实现算法。     

Sets of One and Higher Dimensional Welti Codes and Complementary Codes

A Welti code is a binary sequence with an impulse-like autocorrelation function. A set of such codes may possess vanishing cross-correlation functions. The elements of Welti codes must be members of a set of at least two orthogonal vectors or subcodes. First, methods for synthesizing sets of one-dimensional Welti codes with vanishing cross-correlation functions, and conditions upon their existence are discussed. Then, construction methods of sets of two and higher dimensional Welti codes are presented. Based on these constructions, further sets of mutually orthogonal complementary codes in one or more dimensions can be derived. The use of such signals relates to various topics such as communication, radar and navigation systems, measuring and identification in one or higher dimensional systems, synchronization and spatial alignment, or coded aperture imaging.     

基于Kalman滤波的高频CW电报信号自动识别

针对强噪声背景下高频CW电报信号检测算法性能严重下降、误码率较高的问题,文章提出一种基于卡尔曼滤波的高频CW电报信号同步检测识别算法。利用自同步法对CW电报信号实现位同步,进而利用卡尔曼滤波针对时变干扰噪声设置自适应阈值,对信号能量进行软判决,实现CW电报信号的自适应跟踪检测,提取有效信号进行识别。通过短波信道仿真软件和实际短波通信测试表明,该算法能够在强噪声背景下有效检测识别CW电报信号,且算法可由迭代实现。     

Radar sensor using low probability of interception SS-FH signals

One of the best known weakness of radar sensors in defense and security applications is the necessity to radiate a signal, which can be detected by the target, so being possible (easy in fact) that the target is alerted about the presence of a radar before the radar is alerted about the presence of a target. In this context, Low Probability of Interception (LPI) Radars try to use signals that are difficult to intercept and/or identify. Spread spectrum signals are strong candidates for this application, and systems using special frequency or polyphase modulation schemes are being exploited. Frequency hopping, however, has not received much attention. The typical LPI radar at this moment of the technology is a CW-LFM radar. The simplicity of the technology is its best point. Polyphase codes, on the other hand have the inherent advantage of high instantaneous bandwidth regardless of observation time. But the complexity of the hardware is also higher. FH signals have traditionally been considered of lower performance but higher complexity, due to the difficulties to compensate the individual dopplers for the individual range cells in the receiver. One important point is that an FH radar must be clearly distinguished from an agile frequency radar. In the latter, a pulsed signal is transmitted using different frequencies from pulse to pulse. In an FH radar the frequency changes must be during the pulse. In fact, in an LPI FH radar, a CW frequency hopped signal is used. A radar system concept is proposed in which it shows how these problems can be overcome in a tracking application. Also, the signal format is analyzed under the scope of future decade digital interceptors, showing that, in fact, this kind of signal exhibits improvement in some performances and requires a hardware that is only slightly more complex than that needed for CW-LFM systems     

On Clutter Modeling and the Spectra of Two-Dimensional Gauss-Markov Random Signals

The spectral properties of two-dimensional isotropic clutter signals are examined for the cases in which 1) the clutter has an exponential spatial autocorrelation function, and 2) the clutter is a two-dimensional Gauss-Markov random signal. The one- and twodimensional power spectral densities before and after antenna filtering are obtained, and some of the differences and similarities between these two models are discussed in the context of spectral analysis.     

Adaptive Array Behavior with Periodic Envelope Modulated Interference

A method is presented for determining the effects of envelope modulated interference on a least mean square (LMS) adaptive array. The interference is assumed to have periodic envelope modulation with a bandwidth that is small compared with the carrier frequency. For such interference, the method allows one to calculate the periodic steady-state behavior of the array weights and the resulting array performance. As an example, we compute the effects of an ordinary amplitude modulated (AM) interference signal on the array. It is shown that such interference causes the array to modulate the desired signal envelope but not its phase. With a differential phase-shift-keyed (DPSK) desired signal, AM interference is found to have about the same effect on bit error probability as CW interference.     

基于周期LFM本振的同步Nyquist折叠接收机 多分量信号参数估计算法

 Nyquist折叠接收机(NYFR)为一种新型侦察接收机结构,可利用单/双片模数转换器(ADC)同时完成多Nyquist区域内的宽频段信号采集。本文对NYFR结构进行了改进,提出了多分量信号的参数估计算法。首先,引入了同步结构,对NYFR进行了改进,得到了同步NYFR(SNYFR);其次,以本振为周期性线性调频(LFM)为例,分析了多分量信号的输出结果;然后,提出了去斜函数(DF)以用于检测信号的Nyquist区域;最终,根据区域信息完成了信号的各参数估计。计算量分析与仿真表明,所提算法计算量小且在信噪比(SNR)优于-9 dB时性能已接近克拉美-罗(CRLB)下限。     

Poly-phase codes and optimal filters for multiple user ranging

A technique is introduced to select poly-phase codes and optimal filters of a pulse compression system that have specific temporal and frequency characteristics. In the particular problem under study, multiple vehicles are assigned unique codes and receiver filters that have nearly orthogonal signatures. Narrowband users, that act as interference, are also present within the system. A code selection algorithm is used to select codes which have low autocorrelation sidelobes and low cross correlation peaks. Optimal mismatched filters are designed for these codes which minimize the peak values in the autocorrelation and the cross correlation functions. An adjustment to the filter design technique produces filters with nulls in their frequency response, in addition to having low correlation peaks. The method produces good codes and filters for a four-user system with length 34 four-phase codes. There is considerable improvement in cross and autocorrelation sidelobe levels over the matched filter case with only a slight decrease in the signal-to-noise ratio (SNR) of the system. The mismatched filter design also allows the design of frequency nulls at any frequency with arbitrary null attenuation, null width, and sidelobe level, at the cost of a slight decrease in processing gain     

Noise Injected into Coherent Carrier Signals by Random Phase Changes

The autocorrelation and power spectrum of spurii arising from periodic random phase injections into a coherent backscatter signal are found. Design considerations of appropriate filters to eliminate spurii noise is discussed.     

Hybrid discriminative/class-specific classifiers for narrowband signals

The class-specific (CS) method of signal classification operates by computing low-dimensional feature sets defined for each signal class of interest. By computing separate feature sets tailored to each class, i.e., CS features, the CS method avoids estimating probability distributions in a high-dimension feature space common to all classes. Building a CS classifier amounts to designing feature extraction modules for each class of interest. In this paper we present the design of three CS modules used to form a CS classifier for narrowband signals of finite duration. A general module for narrowband signals based on a narrowband tracker is described. The only assumptions this module makes regarding the time evolution of the signal spectrum are: (1) one or more narrowband lines are present, and (2) the lines wandered either not at all, e.g., CW signal, or with a purpose, e.g., swept FM signal. The other two modules are suited for specific classes of waveforms and assume some a priori knowledge of the signal is available from training data. For in situ training, the tracker-based module can be used to detect as yet unobserved waveforms and classify them into general categories, for example short CW, long CW, fast FM, slow FM, etc. Waveform-specific class-models can then be designed using these waveforms for training. Classification results are presented comparing the performance of a probabilistic conventional classifier with that of a CS classifier built from general modules and a CS classifier built from waveform-specific modules. Results are also presented for hybrid discriminative/generative versions of the classifiers to illustrate the performance gains attainable in using a hybrid over a generative classifier alone.