摘 要

現(xiàn)代先進武器系統(tǒng)的發(fā)展和高技術(shù)戰(zhàn)爭條件下的復(fù)雜戰(zhàn)場環(huán)境，對雷達(dá)目標(biāo)識別具有越來越強烈的需求。在多目標(biāo)跟蹤系統(tǒng)中，由于對雷達(dá)資源的節(jié)約利用及信號處理和計算機技術(shù)的飛速發(fā)展，需要對雷達(dá)資源的節(jié)約利用, 由于信號處理和計算機技術(shù)的飛速發(fā)展，目標(biāo)識別所要求的實時處理已成為了可能。一方面對目標(biāo)進行初步的目標(biāo)識別，建立以及更新目標(biāo)特征數(shù)據(jù)庫，以進行目標(biāo)特征匹配來實現(xiàn)點跡-航跡相關(guān)處理；一方面可以提高建航的快速性，另一方面可以在保證目標(biāo)不丟失的情況下，提高跟蹤的目標(biāo)數(shù)目，大大降低虛警率的同時也保證了航跡質(zhì)量。
本文首先從點跡處理入手，詳細(xì)分析了目標(biāo)點跡特征智能提取的方法，主要包括點跡檢測、點跡凝聚（距離上和方位上）以及智能特征提取等。并對不同目標(biāo)的特征信息進行分析，并進行目標(biāo)分類，創(chuàng)建目標(biāo)特征數(shù)據(jù)庫。然后，根據(jù)前端的點跡數(shù)據(jù)特征信息來進行智能航跡處理，詳細(xì)分析了智能航跡處理的算法實現(xiàn)。本文所提出的智能高效的航跡處理算法是針對目前航跡方面遇到的現(xiàn)實性的問題而提出的，經(jīng)驗證實是切實可行的解決方案。
本文對點跡的智能特征提取和智能航跡處理方法這一過程進行了硬件實現(xiàn)。首先，我們給出了硬件實現(xiàn)框架，對硬件實現(xiàn)的各個步驟給出了詳細(xì)說明。并且重點介紹了SPU硬件處理平臺，它是一種基于雙DSP+FPGA架構(gòu)的高性能的功能強大的板卡。同時，給出了基于TI公司的TMS320C6455DSP的點跡智能特征提取和智能航跡處理的軟件實現(xiàn)流程圖。最后，對某型雷達(dá)的實測數(shù)據(jù)處理，驗證了本文所提出的方法的有效性，并且具有很高的工程實用價值。

關(guān)鍵詞 航跡起始；目標(biāo)識別；目標(biāo)智能特征提??；雙DSP+FPGA


Abstract
Modern and advanced weapons systems development and high-tech warfare complex under the conditions of the battlefield environment have an increasingly strong radar target identification Strong demand. Of the proposed intelligent and efficient processing algorithms for the current track track encountered the reality of the problem Proposed, is a proven practical solutions. In the multi-target tracking system, the need for economical use of radar resources as the signal processing and the rapid development of computer technology, target identification required real-time processing has become possible. On the one hand Target initial target identification, target characteristics to establish and update the database for matching to achieve the target feature points - Air phase Off processing; one can improve the rapid construction of aircraft, the other to ensure that goals are not lost in the circumstances, improve tracking The number of targets, greatly reduce the false alarm rate, while also ensuring the track quality. This article first track from the point of starting treatment, a detailed analysis of The target track features intelligent extraction methods, including point of trace detection, point trace gather (distance and azimuth), and smart Feature extraction, and different characteristics of the target information analysis, and target classification, target characteristics to create a database. However, According to the front of the trace point feature information for intelligent data handling track, a detailed analysis of intelligent algorithms that track the real deal now.
In recent years, with the digital signal processor (DSP) chip integration, computing speed, data throughput and other performance continues to improve; DSP in high-speed, real-time signal processing has been more and more applications, which is smart track the implementation process as possible. This paper describes a DSP + FPGA architecture based on dual-track process of intelligent hardware platforms, including DSP chip chosen TI's TMS320C6455, FPGA selected Altera's EP2S90F1020. In the code composer studio software development environment, through hardware design and software programming intelligent track processing algorithms. Hardware design, including the connection between the module and the module initialization method. Software design and programming, including the main program interrupt response and other routine design.

Key Words Track Initiation; Target Identification; Target Feature; Double DSP+FPGA



















































目 錄
摘 要 I
Abstract III
縮略詞語表 IX
第1章 緒論 1
1.1 概述 1
1.2 課題背景及意義 2
1.3 研究現(xiàn)狀及發(fā)展趨勢 4
1.4 研究內(nèi)容介紹和文章結(jié)構(gòu)安排 5
第2章 雷達(dá)目標(biāo)點跡數(shù)據(jù)形成與處理 7
2.1 概述 7
2.2點跡檢測 7
2.3 點跡數(shù)據(jù)分析及目標(biāo)分裂 8
2.3.1目標(biāo)點跡數(shù)據(jù)在距離上多值分析 9
2.3.2 目標(biāo)點跡數(shù)據(jù)在方位上的多值性分析 10
2.3.3 克服目標(biāo)分裂的方法 11
2.4 目標(biāo)原始點跡數(shù)據(jù)的分辨與歸并 12
2. 4.1 剔除異常的目標(biāo)原始點跡 12
2. 4. 2 點跡數(shù)據(jù)在距離上的歸并與分辨 12
2. 4. 3 點跡數(shù)據(jù)在方位上的歸并與分辨 13
2.5 目標(biāo)點跡凝聚處理 13
2.6 智能特征提取 15
2.7 雷達(dá)目標(biāo)特征信息 16
2.8 小結(jié) 20
第3章 雷達(dá)數(shù)據(jù)的航跡處理 23
3.1 概述 23
3.2 常用的跟蹤濾波器 23
3.2.1 濾波器 23
3.2.2 Kalman濾波器 26
3.3 目標(biāo)跟蹤的航跡起始 27
3.3.1 目標(biāo)識別概述 28
3.3.2 修正的Hough變換 31
3.3.3 ..