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Detection and track of the weak trajectory in the Bearing-Time Record (BTR) is an important method to discover and localize the target automatically in passive sonar. An algorithm to detect and track the trajectories of multi-targets in the BTR is proposed in this paper. It doesn't need the number of targets as prior information, and initial or terminate the trajectory automatically. The tracking of each trajectory is independent and can be parallelized. The detection performance is analyzed by the simulation. The effectiveness of this algorithm is also shown by a real acoustic data from experiments on the sea.

A method is proposed for estimating time delay between MFSK signals received at two spatially separated sensors. onsidering the periodical characteristic of the peaks of cross correlation, the proposed method combines window echnology and differential magnitude between cross correlation and its Hilbert transform. The time argument at hich the differential magnitude achieves the peak in the range of window is the delay estimate. The method is ompared with several other methods. Simulation results show that the proposed method can get better performance. nder certain conditions the performance of proposed method can be better than CRLB by using priori information bout the transmitter and receivers.

The detect and track of the weak target in Bearing-Time Record (BTR) was studied in this paper. The distribution of the measurements of the BTR was derived. And a method of track before detect algorithm based on Hidden Markov Model was given. The simulation and the experiment with real acoustic data showed the effectiveness of this method. The performance of the two classic algorithms Viterbi and Forward-Backward to solve this problem was also compared.

In multiple source detection of using an array, the threshold of the generalized likelihood ratio test (GLRT) is only related with the noise power. And the false alarm probability will increase when one signal is present in the sidelobe of beamformer's pattern because of energy leakage. A constant false alarm ratio (CFAR) based multiple-source detection algorithm was proposed in this paper. The detection probability and false alarm probability were analyzed theoretically and by simulations, and the threshold setting method was given out. The simulation showed the algorithm proposed can detect out the multiple signals effectively and the false alarm probability keeps constant.

The Over-the-Horizon Radar (OTHR) is an effective approach for long-range target detection. However, most existing OTHR systems resort to receive array with quite large aperture, which makes them difficult to deploy. Based on the small aperture receive array, this paper presents a new architecture of long-range target detection system. The shortage of small aperture receive array on echo signal-to-noise ratio (SNR) and beamforming is analyzed theoretically and evaluated through some experiments. To improve the performance, we make some suggestions on the design of transmit waveform, virtual array, and signal processing on high resolution spectral estimation.

In this paper, a novel DOA estimation method without angles pre-estimating for Wideband Signals is proposed. The main idea is to design a novel Direction-Free focusing matrix using the decomposed representation of the array manifold matrix, where the angle parameter is separated from the array geometry and the frequency parameter. The focusing matrix is derived using a method similar to RSS. The novel method also uses the Toeplitz approximation algorithm to improve the estimation performance. The proposed method combines the RSS method and Toeplitz approximation algorithm, and does not require initial angles, so it can be called Toep-DFRSS method. The performance of Toep-DFRSS and other major methods is compared through computer simulations. The simulations show that Toep-DFRSS method has a better resolution performance and estimation accuracy than conventional RSS method, especially in the case of low SNR.

Frequency hopping signals have been widely used in military and civilian applications during the last few decades. It's of great value to locate emitters of frequency hopping signals, especially in military operations. Localization by time difference of arrival (TDOA) is a passive location method of good accuracy which utilizes the differences between the arrival times of signals received by multiple receivers at different sites. Many researches have been published on TDOA estimation algorithms for signals in passive location systems, but there have been few results in the literature about the TDOA estimation accuracy of frequency hopping signals. In this paper, a novel Cramer-Rao lower bound(CRLB) of TDOA estimation for frequency hopping signals is proposed and derived based on the given frequency hopping signal model. Theoretical analysis has revealed how frequency hopping signals' parameters, such as signal band, channel interval, hop duration and signal-to-noise ratio(SNR), affect the estimation performance. Simulation results have justified the theoretical derivation.

This paper presents a new detection method for unknown frequency hopping (FH) signal, this indirect method is base on multiple image features. We first process the time- frequency spectrum of the received signal, extract image features after image segmentation and filtering operations, then establish FH signal verification and joint parameters estimation (FHSV- JPE) mathematical model to describe the detection problem, we propose an optimal solution of the model, and analyze the performance of the algorithm at last. Simulations are carried out to demonstrate the efficiency of the proposed algorithm. I. INTRODUCTION Frequency hopping (FH) communication have received ever increasing attention over the past years as numerous applica- tions have adopted this scheme. With this increased use of FH communications, naturally, came the question of detection. This question has given rise to a considerable amount research focused on the detection of FH signals. Those researches can be classified into two kinds: searching detection methods and software detection methods. The former include methods in papers (1)(2)(3) . This kind of methods needs information of many FH parameters. The latter kind of methods includes ex- ponential averaging algorithm (4), algorithm based on wavelet transformation (5) and so on. The signal models in these methods are ideal without considering short-time burst signals in practical environments. This paper presents a new indirect detection method for FH signals. Compared with previous researches, this method has two new ideas. Firstly, it introduces image processing into FH signal detection, which makes the feature extraction more stable and credible. Secondly, it establishes the FH signal verification and joint parameters estimation (FHSV-JPE) model, which can be used to verify the existences of FH signals and analyze detection performance in theory. This paper is organized as follows. In Section II, we describe the receive signal model. The extraction of image features is proposed in Section III. Section IV establishes the FHSV- JPE model and gives out its solution. Performance analysis is presented in section V. The simulation results are illustrated in Section VI. The conclusions are given in the last section.